Career | DEZERAECOX

Investigating the Investigators: 2020 Edition

Tue, 16 Mar 2021 19:00:00 +0000

Investigating the Investigators: 2020 Edition

Each year the Australian National Health and Medical Research Council award a set of Fellowships to outstanding scientists. As an Early-Career Researcher, you might say I have a vested interest in understanding the picture these outcomes paint for my ability to pursue a research career in Australia. I’ve written extensively about how the outcomes reflect trends of the scheme as a whole (you can find a detailed description of the , and a ). But this still begs the question: just what does a successful Investigator look like in my field and at my career stage in 2020? And perhaps even more importantly for you, what did a successful application look like amongst your peers? So, this year I’ve decided to put the data in your hands!

Introducing the portal

Meet : a collection of interactive datasets underlying the NHMRC outcomes across four key metrics - Research area, Geography, Seniority and Gender. You can now explore how the Fellowship scheme has evolved with time, how the most successful research hubs are distributed, and what characteristics are typical of successful applications within each funding tier. The landing page includes everything you need to know to get started, as well as some resources for the extra curious among you.

A few words on why…

These Fellowships are the life-blood of many Australian researchers, and are always hotly-contested tickets for emerging and established researchers alike. Astoundingly, given the absolute reliance on data when it comes to everyday science, very little is done with the outcome data beyond cursory summaries of gender and career stage equity. Researchers deserve to know what the overarching trends are and how the scheme has evolved. Now, the interactive and wholistic nature of the datasets means that you no longer have to take my word for it (or anyone else’s for that matter!). In addition, my hope is that the portal will be a step toward maximizing access to actionable insights for researchers looking to develop their future funding strategy.

Final thoughts

Researchers are already busy preparing applications for the next round of Investigator Grants which close in just a few short weeks, and this year the stakes are perhaps higher than ever before. As , external funding sources will be paramount. For ECRs especially, the next few years look bleak as we are at without dedicated support.

With outcome data directly in the hands of researchers, everyone has the opportunity to make data-driven decisions about where their energies are best spent next application season. Most importantly, these data offer us as a community the opportunity to evaluate how well the scheme outcomes are aligned with our priorities for supporting innovative and emerging researchers as the future of Australian science.

So, without any further ado…. If you haven’t already, head on over to . Happy exploring!

Are you thinking of applying in the next round of Investigator Grants? Did any of the datasets surprise you, or were they helpful in your decision of whether or not to apply? Head over to the , or let me know on !

Image credits: inspecting gears with magnifying glass | @ pluyer via

Year in review: 2020 Edition

Sun, 14 Mar 2021 10:40:50 +0000

Year in review: 2020 Edition

2020 was… A year that felt like a decade, but with the productivity of a boozy long weekend. In case you haven’t been on planet earth for the entire year (hello friend, teach me your secrets), it was of course the year in which a coronavirus (specifically SARS-Cov2) emerged and rapidly took over the globe.

The ensuing pandemonium was slow to build, and even slower to resolve. In fact, most countries around the world are still living with some form of social restrictions aimed at controlling transmission and preventing severe infection. We’ve since entered a recession, predicted by many to be the largest since the global financial crisis. Most importantly, many people lost their lives to the virus, and many more still have a severe and long-lasting illness.

I am fortunate enough to live in a country with very low infection rates and virtually no community transmission, and so life has returned to a post-virus normal. But (of course, there is always a but) to achieve this hefty goal, we as a community endured the longest and harshest lockdown conditions seen anywhere around the globe for almost a year. Make no mistake; it was essential and worthwhile. However, it was also eye-opening, isolating, disruptive and challenging. And as well as being a bench biologist who couldn’t get to the bench, I faced the lockdown separated by state borders from my partner, family and friends. To say it was mentally tough would be a colossal understatement, and despite this I am well aware of many who faced worse than me.

So, in acknowledging that no two experiences of 2020 were alike, I decided to stick with my traditional by-the-numbers account of the past year. You’ll find wins few and far between, more than a handful of losses, and a list of goals that looked a little different from start to finish. Finally, I look to the future and set my sights on recovery in 2021.

Wins

A snapshot of the high points

I survived 2020. I think that certainly belongs in the win column, don’t you?
I read three books, and reviewed one.
I published five blog posts totalling 6500 words, which were viewed 1557 times by 833 different visitors from more than 10 countries
I contributed my first to an online publication
I published my first , providing analysis tools for researchers considering applying for NHMRC funding
I worked over 2500 hours, more than 40% of which went towards submitting my first first-author postdoctoral paper for review to a top-tier journal
Five manuscripts I contributed to were officially published
I slept an average of 7 hours and 5 minutes
I overhauled my entire organisation system, from code to experiments to publications
I created and published not but science-communication videos as part of my first official scicomm training worskhop
I organised and hosted 17 Departmental seminars from a diverse group of researchers spanning career stages and countries - and made a successful transition to virtual when the pandemic hit!
I gave 2 invited seminars, and attended 3 virtual conferences

Losses

A not-so-snappy shot of the low points

Another year with no published first-author manuscripts, despite furiously writing for most of the year
My first-author paper was rejected from 4 different journals before even being sent out for peer review
Almost one fifth of the hours I worked were spent on emails and other administrative tasks
I didn’t write a single grant or application
I downloaded 1084 papers, and read less than 10% of them
I started 4 books that I didn’t finish
I didn’t publish blog posts in 7 out of 12 months
My coding projects are still still in a state of disarray, in desperate need of a tidy and some documentation
I only averaged 3817 steps per day
I was, perhaps, 50% productive on any given day

Lessons

The bits I wish I knew at the start of 2020, but had to learn the hard way.

Selfish isn’t a dirty word - for much of 2020 I struggled with the feeling of being a bad friend, bad partner, bad lab mate, bad family member as I weathered the storm of Victoria’s lockdown alone. I was lonely, unhealthy, unmotivated and struggling to keep my head above water and still I felt uncommitted to the many relationships in my life I let languish during this period. But in reality, I didn’t have anything to give - and I needed to be selfish, to rebuild my own mental health, to redefine my sense of self in this weird and wonderful (?) new world we were suddenly inhabiting. And it took me a long time to be ok with this idea of a self-centred approach to wellbeing. After all, you can’t pour from an empty cup.
Working from home and living at work are two entirely separate things - At the start of 2020 there was an abundance of tips about productive workspaces, setting routines, engaging in your normal ready-for-work activities, setting aside time each day to step away from work…. As someone who has had the luxury of a few work-from-home days in the past that yielded astounding levels of productivity, I was initially optimistic about the opportunities a few onths of working from home presented. It was only a few weeks into what would turn out to be a year long work-from-home order, before I realised how sorely mistaken I was. This was not the quiet, focused time I had enjoyed pre-pandemic, but clouded, overcast and gloomy time spent doom-scrolling, feeling unengaged and unenthusiastic about the prospect of another day spent alone in my home-office. It was a few months in that I came across the phrase living at work, and it struck home how insidiously this transition had happened. Despite having a separate work space, work never really left my home space in the way that I could leave the work office, and I came to realise how important the role of our choice is in this regard.
Variety is the spice of life - Ok, I know this one is a little cliché. And yet, if you’d asked me a year ago I would have adamantly told you that I am a person who is fond of organisation, planning and routines. From breakfast meals to shampoo brands to pens to friends - I am a creature of habit. I know what I like, and I surround myself with it. I structure my time. I plan and organise weeks, months, years in advance and I work toward goals with almost singular focus. And yet, this year almost every single one of those things was thrown completely out the window. It was impossible to plan a week in advance (or even a day sometimes). I found myself missing those spontaneous interruptions to my calendar or walks for coffee with random colleagues during the day. I missed the variety of faces on the tram each morning, and instead sought out variety in walking routes to new cafes for lunch as a poor surrogate. Most vividly I missed the usual spontaneity of a week in bench research science. Normally, each day is subtly different - a different experiment, or technique, this meeting versus that meeting, a new piece of code to work on or a new manuscript to write. Instead of this variety, life became a blur of zoom meetings, trudging forward on a single manuscript, and trying desperately to halt my doom-scrolling as we awaited daily case numbers and press conferences. I will never again take for granted the motivation a varied work day brings to my passion for science.

Goals

As with much about 2020, my goals unfortunately went promptly out the window around June. Even still, I finally submitted the first of three first-author postdoctoral research papers, and successfully created a growing community of Happy Hacker scientists who are learning to code. I started semi-regular yoga and implemented a new morning routine focused on engaging mindfully with the day ahead. While my writing here lagged severely, those posts I managed to write and publish are some of those I am most proud of. None of these things went according to plan, and it certainly wasn’t a glamorous insta-worthy road to ticking boxes. And yet, here we are, moving forward ever so slightly. So where to from here?

Papers are paramount. Déjà vu aside, with drafts still floating around in various states of disarray the first half of 2021 demands some serious focus on wrapping up the next two manuscripts. Using structured writing time of at least twenty hours a week, my goal is to have submitted the remaining two manuscripts before starting my next postdoctoral position mid-year. While last year writing sessions were often sidetracked by more ‘pressing’ needs, this year I will plan each session in advance, using calendar entries for accountability and a master task list for assigning goals and tracking progress.
Revamp the reading routine. Last year I hinted at a timely review of how I consume scientific literature. I’ve often pushed reading to the end of my to-do list and settled for skimming daily email alerts or saving an article or two from Twitter with some handwavy expectation of actually reading them. Instead, I want to not only find time for an engaged reading practice but also give myself space to really think about what I am reading, parlaying this into more (and better!) scientific insights. I will implement two reading sessions per week, drawing pre-selected articles from my ever-growing pile of exciting new material. This will be tracked using a database, which simultaneously enables detailed cross-connection between individual resources and developing insights and ideas within overarching project themes.
Commit to coding cleanup. One of the few positives to come from a year of working from home, coupled with a freshly-submitted manuscript combing computational analyses of wet-lab experiments, was a rapid expansion and solidification of my amateur coding skills. I am often pleasantly surprised when I realise just how far these skills have developed, and it makes me even more excited to pass them on during Hacky Hours each week. And yet, two packages I first wrote more than four years ago still languish, lacking love and in desperate need of refactoring. This is the year I commit to cleaning up these packages. I will spend an hour each week tackling small chucks, which will be tracked using GitHub issues and measured in milestones.
Invest in intentional. Sometimes a week can pass by and I barely realise due to a blur of endless triaging. These type of weeks tend to feel like an old-school cartoon where my wheels are spinning yet the car is going nowhere fast. My goal is to understand (and correct) my balance between the urgent but unimportant tasks that often fill my day (hellloooo email, I’m looking at you…), and the essential but non-urgent tasks that will be of most tangible benefit long term. Beyond task management, I will start each morning by writing down three intentions for the day, using these to anchor how my time is spent and as a record for reflection. I will also frame these intentions within the time management matrix, to ensure I am investing in long term progress by hitting small milestones each and every day.

2020 was without a doubt challenging and confronting and, just between you and I, 2021 was not looking to be off to a great start. After handing over my role in Melbourne and leaping out of my comfort zone, I landed in limbo - awaiting a revised start date for my international Fellowship, unemployed and uncertain of my direction for the first time in over a decade. And yet, here I am daring the universe by setting goals for the year ahead. From here, 2021 is about regrouping, recovering and recalibrating, readying for reentry to the world post-COVID. And I couldn’t be happier to have you along for the ride.

Image credits: @brookelark via

Learning to code: it's as easy and as complex as that.

Sun, 05 Jul 2020 15:12:56 +0000

Learning to code: it’s as easy and as complex as that.

Many life scientists have used their time under pandemic-induced lockdown to learn their first programming language. Yay! Coding has many many advantages (reproducibility, more complex analyses, reusability, time-saving) that I have espoused all too many times before.

Many people start with a tutorial or two, then jump straight in and analyse a dataset. They get a plot, maybe a few statistics and voila! They are now scientists who can code.

Kinda.

See, the thing is there is more (much more) to implementing programmatic workflows in a biological context. Unfortunately, these are the skills that intro-to-programming courses often fail to teach you (or sometimes even mention) - but without them, adding scripts to your workflow can often make your work less reproducible, not more. For the sake of the argument, lets pick one.

Version control.

Imagine a bowl of spaghetti (lots of lines of code), which you admire briefly before throwing at a canvas (your interpreter). You create a beautiful work of art (your plot), and stand back to admire your handiwork. Maybe you show it to a few friends, and they are super impressed. (Awesome!). And then they ask - how did you do it? Not just the throwing motion, or the rough distance between the bowl and the canvas. They want to know the precise location of every single strand of spaghetti in the bowl before you threw it at the canvas. They want to know the recipe you used for the sauce, down to the precise number of grams of oregano.

Now, of course, we aren’t actually talking about a bowl of spaghetti - we are talking about your code. So - of course - you can simply show them the script! Huzzah! The precise instructions that enabled you to make that very specific plot. But here’s the kicker. The code is not static. In fact, chances are that you poured over it for hours (maybe days) adjusting, tweaking, changing, testing and rerunning - all to get the glorious, awe-inspiring plot at the end.

By this stage, you’ve probably made over 100 spaghetti-splattered-spectacles (plots) and your house is starting to smell like an Italian Pizza joint. If I asked you to produce the exact recipe, down to the very position of each strand of spaghetti, for plot number 47 - could you do it?

My guess is probably no.

Conducting experiments is at the heart of science. However, without the essential extracurricular activities like maintaining backups, organising your results files and optimising project management systems, you wouldn’t last very long in academic research. The same is true of coding. Learning to write a functioning script is just the tip of the iceberg when it comes to implementing reproducible computing workflows in biology.

So, with this in mind, what are those all important skills you ask? Well, luckily, far more experienced scholars than I have written on this topic and provided guides (like and ) for those starting out in the computational space. These are highly applicable to biologists learning to code, and I encourage you to check them out before you stray too far down the spaghetti-on-the-wall path (like I did). As with any system, it is easiest to implement new routines before you have become to set in the old ones! At the very least, here are a few things to consider:

, including Github/GitLab/BitBucket
, including efficient folder layouts
and docker containers
practices
, including repositories and citing software you use

For more, make sure you check out the resources below.

Oh, and one last thing.

Unfortunately, this type of organisational work is not typically measured as a key performance outcome for biologists. Your number of git repositories or test coverage for an analysis suite is unlikely to come up in an award nomination or promotion application. And yet, it is entirely crucial as we move toward bigger and more complicated data and analyses - and so I encourage you to take the time to learn anyway. Maybe one day it will be recognised as essential work by the powers that be - but until then, at the very least, it remains essential for anyone wanting to do good reproducible science. And who doesn’t want that?

Final thoughts

So you want to learn to code? Yes - do it, 100%. I honestly couldn’t recommend or encourage it more. But please do so mindfully. If you want to have the best possible chance of integrating this wonderful tool into your scientific ecosystem in the long-term, you have to lay solid foundations and develop sustainable practice/methods.

Have you used any of these techniques as a budding bench-to-bytes biologist? Find me on or head over to the to tell me more!

Resources:

Image credits: Tomwsulcer via & olamishchenko via

A year in review: 2019 edition

Fri, 31 Jan 2020 12:46:00 +0000

The holiday season is a time of reflection for many, me included. However, this was heightened this year, and somewhat hijacked, by the looming start of a new decade.

While there are plenty of discussions of why 2019 isn’t the end of the decade (like , and ), it did little to stem the tide of ten-year progress reports flooding . These outpourings of academic (and personal) success are often incredible and inspirational, but can also be overwhelming and disheartening for those of us who feel less accomplished.

So as is tradition, I decided to stick with my by-the-numbers account of the past year. You’ll find some wins, a handful of losses, and a few goals that looked a little different from start to finish. Finally, I look to the future and set my sights on kicking brand new goals in 2020.

Wins

A snapshot of the high points

I contributed to 4 manuscripts, of which 3 were posted as preprints
I completed my first independently-funded research project using funds totalling $40 000
I was awarded ~ $10 000 in travel awards
I attended 4 national and 2 international conferences
I presented 5 research talks, 2 posters and chaired an academic career development panel
I gave my first invited research seminar at my alma matta
I was awarded an international post-doctoral fellowship (!)
I performed over 45 (mostly week-long) experiments in just 159 working days, and over 75% of these gave useable results
I wrote or edited over 30 000 lines of code
I was an active member of 4 conference and professional committees, and an ordinary member of 4 professional societies
I directly supervised 3 students and informally mentored at least 4 others
I attended a 5-day leadership course, making 5 new connections that have blossomed into 3 new collaborative relationships
I accounted for each of my working days by posting a reflection to a purpose-built Instagram profile, receiving a total of 3191 likes
I authored 10 blog posts containing a total of 14 642 words, which received 5437 views from 3849 visitors across 36 different countries - more than half of these views were on a single post after I shared it with the Twitterverse!
I slept an average of 7 hours a night, did an average 6260 steps per day, and lost 12 kilograms
I read 1 1/2 more books than last year and completed 1/4 of my first ever attempt at cross stitch
I gave my very first tech talk at a local meetup group
I travelled to 3 countries and explored 5 new cities, and took 2571 photos
I spent 365 days being a partner, sister, colleague and friend - being a happy, (mostly!) healthy human

Losses

A snappier shot of the low points

Only one manuscript made it through the review process to be published
None of my first-author manuscripts are any closer to being submitted
Of the 431 papers I downloaded, I read less than 10% of them in full
I am not proud of my ‘bedside manner’, as I was impatient and frequently frustrated with students
I spent over 50 hours preparing 5 unsuccessful grant or fellowship applications
My coding projects are still in a state of disarray, in desperate need of a tidy and some documentation
I only read 3 1/2 books and put 12 kilograms back on
There were days where I barely slept 4 hours and struggled to make 1000 steps
I only took 11 days of leave, and was fuelled by stress and anxiety far more often than passion and curiosity

Lessons

The bits I wish I knew at the start of 2019, but had to learn the hard way.

You have to crawl before you can walk - academic conferences are great, especially the chance to travel internationally. However, you have to have the time and effort already committed to a project to have something new and interesting to present, and in turn to make the most out of the experience.
Time tracking - the more you know! There are already people using your personal data to sell you shoes and expensive holidays - why not use your personal data for good, not evil? Late in 2019, I started tracking how I spend my workday (keep an eye out for more details coming soon!), helping me refocus on my goals, dedicate productive time to important work and better plan my time for specific activities according to how long it had taken in the past.
The sunk-cost fallacy - Sometimes you have to cut your losses and move on, despite having invested so much time and effort and energy into one particular thing. If it’s not right, or not happening, maybe it never will be. And that’s ok - sometimes you have to empty some space to leave room for the next great thing, whether that’s the next big experiment or project, or the next townhouse or friendship. However…
Perseverance is key - every application makes your next application better. Although, being privileged enough to be able to persevere is a huge source of diversity challenge in academia. Appreciate when you have the option to continue chasing a dream, and not just when that dream becomes reality.
Decisions are hard - and making them can change the course of your life immediately, even in how you feel about the people around you.
Some people will never understand - and that’s on them, not you. Living your best life is unlikely to please everyone, so live a life you’re proud of and whether others understand your path or not is irrelevant.

Goals

This time last year I set some goals. This was a new approach to goal-setting for me, and I’m pleased that it worked (moderately) well! Physical activity was a consistent focus - even if only a short walk in the afternoon, I was conscious of the link between how my brain and body feel. I made substantial progress on building reflective practices and, last but not least, I landed the next job!

Building on this foundation, here are my goals for 2020

1. Papers are paramount. With a looming international move, I have a little over six months to tie-up all my projects and get my first-author manuscripts over the line. My goal is to finalise three publication-ready first-author manuscripts by April. With drafts floating around in various states of disarray, I will use structured writing time for at least eight hours a week to make focused progress. I will use calendar entries for accountability and maintain a master task list for tracking progress. I would also like to reorganise my reading and writing process and systems, but that’s a goal for another time!

2. Hacking hand-over. Part of the leadership course I attended encouraged us to think about ourselves as changemakers. This could result from our science, or more broadly our leadership, but nonetheless we were to imagine what change we wanted to make in the world over the next year. Then we had to plan it. Who would we connect with? What skills/tools did we need? I have always been a passionate advocate for programming for life scientists, and I would love to be the catalyst for this in our institute - to take the plan I sketched on paper (yes - real-life butchers paper!) and put it into action. My goal is to establish a local hacky hour at my institute, bringing together experienced, amateur and coding-curious researchers in a collaborative space to learn from each other. I will gather a small working group of researchers experienced in programming by the end of February, where we will brainstorm the best structure, location and time for meetups. The action items from that meeting will serve as a task list for tracking progress, and I will coordinate at least three hacky hours before handing over the reins when I move.

3. Blog better. Despite averaging one post per month last year, I felt there was a lack of substance with so many conference wrapups and few useful, practical or probative posts. The one obvious exception was a rather popular commentary on the state of NHMRC Investigator Grants. This was a combination of an important issue and a good coding project, and I would love to produce more content like this in the future. My goal is to continue posting at least once per month, of which half will pursue practical or probative themes. This will be easily tracked by my posting record here, so feel free to help me stay accountable!

4. Healthy is happy, and mindfulness matters. As I approach another decade of life (that’s right, a big three-oh this year), I am starting to appreciate that a healthy body and mind is not really something you can achieve. There is no box to tick to say you are done, and there isn’t really a finish line. A commitment to maintaining your physical and psychological health is lifelong, and relapses will happen when you aren’t paying attention. My goal is to recover my healthy habits, focusing on yoga and reflections once a week. My progress will be easily tracked by my health app (thanks technology!), and I will continue to maintain my purpose-built Instagram account with weekly posts. For the safety of me and my lab mates, that account will stay anonymous - but it serves as a neat record for me at least!

2019 was undoubtedly one of the hardest, but most rewarding years yet. Just when I finally felt comfortable in my space and role in Melbourne, I landed an international Fellowship - a huge win that is equal parts exciting and terrifying. As they say, life begins at the edge of your comfort zone. So here’s to an adventurous, unknown 2020 - may it be filled with science, self-exploration and smiles.

Image credits: @brookelark via

BioInfoSummer 2019

Sun, 29 Dec 2019 09:28:44 +0000

With half my home state on fire and the lead up to Christmas, this post has been in the works for a few weeks. But here it is - better late than never! My brief recap of my recent adventure to BioInfoSummer 2019.

Conference details

Title:

Date: December 2nd - 6th 2019

Location: University of Sydney, Australia

Overview:

BioInfoSummer brings together advanced undergraduate and postgraduate students, researchers and professionals from the mathematics, statistics, medical sciences and information technology disciplines. Attendees develop bioinformatics skills, national networks and employability. The central themes of the 2019 conference were Epigenetics/genomics, Single cell omics, Mass spec analytics and BioCAsia/precision medicine.

Overall thoughts and impressions

Of all the conference travel I have done this year, BioInfoSummer was the closest to home and the furthest from a normal conference. The wide applicability of omics techniques meant a broad spectrum of research topics presented by a diverse collection of researchers with a common love for data analysis. In addition, being targeted at students and early-career researchers meant the dynamic of the seminar sessions was quite different - an atmosphere in which students were comfortable asking questions and driving the discussion around world-leading best practices in the field of bioinformatics. This was supported by plentiful and generous travel scholarships boosting the participation of interstate early-career researchers.

Even though my research has been edging into bioinformatics for a little while, this was my first formal foray into the community. While I was a little anxious about being immersed in a new group of people, luckily bioinformaticians are a friendly bunch! This meant that the workshops had a welcoming feel, creating a safe space to actively try out the techniques presented during the morning symposium sessions.

Last but not least, the location and timing of BioInfoSummer meant that they were able to share sessions and speakers with , and were followed directly by . This enriched the sessions and provided even greater diversity and networking opportunities. This truly was a fantastic blend representative of the bioinformatics scene in Australia. I cannot recommend enough for new PhD students or post-doctoral researchers new to bioinformatics in it’s many incarnations.

Lessions learnt

1. Bioinformatic techniques for proteomic analyses lags behind the trail blazed by genomics - this was evident in the distribution of the program, but also attendees. However, I also think that…

2. The distinction between proteomics and genomics is sometimes unhelpful - similar underlying data structures make some methods applicable to both, and leveraging the substantial ground that has been covered in genomics will assist in the rapid progression and development of proteomics methods.

3. Single cells are the future, but not the complete story - innovations in single-cell proteomics and ongoing developments in single-cell RNAseq will continue to push the boundaries of our understanding of biology on the smallest scales. However, one of my favourite talks of the conference was on the value of bulk methods in an era of single-cell capabilities. And I agree - these methods should be applied as appropriate and often one and inform the other.

4. Seeing is believing - two-dimensional imaging mass spec and spatial transcriptomics are the next frontier. With these techniques, we are starting to understand the spatial distribution and cooperation of cells in health and disease.

5. The future is now - the big data buzzword - everyone will have heard the term big data. This is becoming more the norm than the exception, even in biological research. This has meant that method development and bioinformaticians are in high demand, and become recognised as an integral part to any research project. This was exemplified by one of the conference keynotes, in which the speaker discussed the essential skills for a bioinformatician in the next five years; many of these included the ability to wrangle, access and store large amounts of data, as well as being able to leverage this data for biological insight.

6. Unexpected acquaintances - I travelled to Sydney expecting to know no-one. In a classic small-science-world moment, within five minutes of arriving I ran into a post-doc from another research group in my building! While we had met and talked a little previously, the chance to spend a week nerding out over data analysis and coding methods was the perfect way to get to know each other better. In fact, this was one of the best parts of the conference. As well as this, I met a handful of people from my alma mata who grew up in a similar corner of the world as I did.

Take home resources

There were too many great resources to share them all, but if you’re looking for tutorial style activities then the Material for each of the is a great place to start. Other than this, below are a few of the packages, tutorials or databases that I am keen to check out after hearing about them during the conference:

’s featured workspaces demonstrate common genomic analysis pipelines deployed using data and tools available on AnVIL.
is a portal to a series of public experiments describing mouse and human stem cells and how they differentiate to become mature cells, tissues and organs.
is a collection of lightweight and handy tools for Python that help to handle various sorts of proteomics data.
: A Python Library for High-Throughput (Phospho)proteomics Data Analysis
The repository contains a list of open source Python tools for Proteomics analysis. The list is very likely incomplete and we are happy to take pull request with new tools.
The workflow management system is a tool to create reproducible and scalable data analyses. Workflows are described via a human readable, Python based language.
workflow: differential discovery in high-throughput high-dimensional cytometry datasets

These will hopefully give you a flavour of the overall themes covered at the conference, but if you are new to the world of bioinformatics I thoroughly encourage you to get involved next year. The conference is slated to be held next December in Canberra, so keep an eye out for the official announcement!

Overall, BioInfoSummer was a great opportunity to connect and build community with like-minded people. I was so lucky to be supported by an AMSI ChooseMaths travel award - without their support, I could not have travelled to attend the conference and I cannot thank them enough for their support of Women in STEM. If you are new to or interested in the world of bioinformatics I whole-heartedly recommend checking it out next year!

Image credits:

Behind the scenes: Investigating the Investigators

Thu, 31 Oct 2019 01:30:27 +0000

The hottest topic on Australian researchers lips of late has been the recent NHMRC Investigator Grant announcement. I recently set about flexing my data-science muscles to see what the outcomes of the scheme were overall, and what a successful application might look like for the next round. If you haven’t come across it yet, you can read more .

Below is a behind-the-scenes look at what went into the data analysis for this post, and what I learnt along the way. I have also released all the code and results as a for those who like the real nitty-gritty details or want to extend the analysis.

Raw data

The raw data used in this analysis came from three main sources.

The first was the , which offers spreadsheet summaries for grants released since 2013. I chose to use only the data from 2015 onwards, for a couple of reasons: (1) the structure of the Fellowship system appears to have changed in 2014 to the ECF, CDF, RF layout which remained in place until 2018. This meant that 2013 data was poorly correlated with the more recent datasets. (2) The 2014 dataset did not have as much detail in the gender, age, state breakdowns that could be easily compared to the following years. (3) Five years seemed like a nice time period to work with!

The second source of data was the Field of Research codes used to classify research. You can find the complete list at the . I struggled to find an easily-downloadable version, and instead copied them from the University of Melbourne intranet. With a little post-processing, I had a fully functional list of each level of classification, which I could then use to understand which types of research were popular for funding.

The last source of data was , which I used to gather the number of research publications and average Field-Weighted-Citation-Impact (FWCI) for each awardee in the ten years previous to their year of award. This was somewhat of a manual process, and I used the ‘best match’ profile for each awardee imported into SciVal. Overall, 88% of the awardees were matched accurately (and this could be increased with a little manual curation). I also did a little digging around in the PubMed Central API using a python package (see the resources list below for more information) to batch-query the author names and collect their publication history, to compare with the matches generated by SciVal.

Processing and analysis

After initial cleaning of the raw data, I then equated the new and old schemes by matching the tiers. Although the correlation is imperfect (due to changes to eligibility between the old and new schemes), this resulted in Early Career Fellowships mapping to Emerging Leader 1, Career Development Fellowships mapping to Emerging Leader 2, and Research Fellowships mapping to Leadership Fellowships.

Lessons learnt

Data is messy. This was evident in all of the raw data I collected - naively, I expected simple-to-use spreadsheets from the NHMRC. At the very least, I was anticipating similar formats for the more recent 5 years. What I was greeted with was a complicated series of tables designed for visual interpretation by human eyes and not easy accessibility via computer scraping. The initial data cleanup took more than half the time it took to complete the analysis.

Through this process, it became clear to me that as a general rule people, despite often working in a science-oriented role, do not handle, label or store data well. With the increasingly data-driven world we live in, we would all benefit from improving our data hygiene.

Lastly, while the trends I saw and commented on are indeed interesting, they should be interpreted cautiously. The data that the NHMRC provides is somewhat fragmented (to protect the privacy of successful applicants). More importantly, the data they do provide is focused on successful applications. There are lots of important details about the makeup of the applicant pool that we don’t see and this is important - albeit missing - context for interpreting the trends I highlighted.

Similarly, publication history searches are a tricky one. Pay-walled publication information is a nightmare to access, and although PubMed searches are OK they are limited. To get standard metrics such as H-indices and field-weighted citation impacts requires access to subscription services. Moreover, people’s names are difficult! Even once you have access to the databases, it can be difficult to know whether/how to split the given names into first/last and there is almost no chance of avoiding manual curation if you want a complete dataset.

Tricks and tools of the trade

As this was my first dedicated data-science style project, I quickly ran across a few questions.

When wanting to plot the per-state distribution of applications and successful awardees, the most obvious visualisation was a map. I’d never plotted a map before, and after a quick google search I found myself asking What on earth is a choropleth and where do I find a shapefile? It turned out a chloropleth is what I wanted to make - a thematic map in which areas are shaded or patterned in proportion to the measurement variable being displayed on the map. And to do this, you need a shapefile - a vector data storage format for storing the location, shape, and attributes of geographic features. Luckily there are a few , and eventually, I found the I was looking for. Amazingly, using meant dealing with this type of data relied on many of the skills I already have and before I knew it Voila! - one map of Australia complete with colour-mapped and labelled data.

While handling the somewhat messy task of linking successful awardees to their publication track record, I came across the problem of slight variations between different naming formats. How do you match text that is fuzzy, and how does Levenshtein help? It turns out that Python has a whole range of functions via the that help to compare strings that are referring to the same thing but are written slightly differently. The most simple version of this makes use of the Levenshtein distance, named after Vladimir Levenshtein who originally considered this phenomenon in 1965. This metric measures how far apart two sequences of words are according to the minimum number of edits needed to change one into the other. These edits can be insertions, deletions or substitutions. One detailed later, and I was on my way matching fellowship awardees to scival authors in no time.

Finally, throughout the whole plotting process, I was conscious of my colour palette. I am a firm believer that good dataviz should be both functional and beautiful. With plenty of gender-based comparisons, you might wonder how I could go past the tried and true colour combination. So why I didn’t choose pink and blue for gender studies? It turns out there are a few reasons why red and blue for gender data is an ‘unawesome choice’ rooted in gender stereotypes (pink = girls = weaky, cute and blue = boys =strong, bold). Luckily there are plenty of good colour-combinations that circumvent these .

With these tools in hand, I had everything necessary to analyse and visualise the datasets at my disposal. To see these tricks and tools in action, don’t forget to check out the or head along to some of the resources listed below.

Resources

Wishlist: I haven’t had a chance to implement this functionality yet but these dataviz tools are high on my to-try list to extend the accessibility of this dataset!

Disclaimer

The original analysis was intended to inform my personal decision of whether to apply for an Investigator Grant in the 2019 round. Any action you take as a result of this information is done at your own peril. If you do decide to act on this information, I wish you the best of luck whichever path you may choose. May the odds be ever in your favour.

This being said, I have of course aimed to be as unbiased and informative as possible. This is also my first foray into data-science-for-public-consumption, so if you do notice any overt errors or bugs feel free to raise an issue on or get in touch via and I will check it out as soon as possible.

Image credits: cadop via

Investigating the Investigator Grants 2019

Mon, 30 Sep 2019 01:26:50 +0000

Introduction

The hottest topic on Australian researchers lips this month has been the recent NHMRC Investigator Grant announcement. After all the commotion around the new scheme and the distribution of research dollars, I set about flexing my data-science muscles to see what the outcomes of the scheme were overall, and what a successful application might look like for the next round.

What are Investigator Grants?

If you are a scientific researcher in Australia, chances are you were aware of the NHMRC announcement a few weeks ago of their latest round of funding. For those who are outside health-focused research, this was a highly-anticipated announcement after a complete re-structure of the NHMRC Funding Schemes over the previous year. The reform included replacing the Fellowship system (funds to support individual researchers to establish their own research programme) under the unified banner of Investigator Grants.

Historically, previous incarnations of these Fellowships (Early Career, Career Development and Research Fellowships) have supported the very best and brightest researchers in Australia with varying levels of lottery-luck in their award. Importantly, having been successful at the first rungs on the Fellowship ladder, researchers were then much more likely to gain the next level of support. Therefore, the award of these Fellowships to emerging researchers is a crucial support system that could make or break a career.

In particular, the lists better support for Early and Mid-Career Researchers (EMCRs) as a key goal of their reform:

Early and mid-career researchers are being discouraged from pursuing a research career.
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In response to these issues, NHMRC reviewed the structure of its research funding and has reformed its grant program.

NHMRC, 2019

Why the fuss?

For researchers who spend many (many) weeks (months) working on the application for these schemes, the outcomes are of intense interest. The research funding environment in Australia is extremely competitive, and often the difference between funded and not funded can be little more than pot-luck. Early reports during the peer review process this year suggested that the new scheme had an abundance of issues and was likely to be even more of a lottery than previous years.

After the announcement, scientists flooded Twitter with their thoughts, interpretations and statistical analysis of the overall outcomes. There were many deserving people who were lucky enough to make the grade this time around. However, there were also an abundance of leading researchers who missed out and cursory analyses highlighted an abundance of inequities and unforeseen results of the reform.

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Many of the numbers you will see online come from the key performance data released by the NHMRC (data on gender, age and state awardee rates has been made available since at least 2013). It is my firm belief that, as scientists, we should use science (including data science) to drive our decision making. The trends reveal biases/underlying issues in the grant scheme, and provide rationale/direction for additional reform. In addition, the profile of previously successful applicants can help researchers like myself understand how we fit within the scheme and, according to whether (or not) we fit the profile, inform our decision to apply in the next round (which is not that far away!).

Crunching the numbers

Most of the raw data used in this analysis came from the . I collected some extra data on the Field of Research codes and individual researchers from additional sources including the and .

After initial cleaning of the raw data, I decided to equate the new and old schemes by ‘matching’ the tiers as best as possible. According to a fact sheet provided by the , equivalent schemes are as follows: Early Career Fellowships map to Emerging Leadership level 1, Career Development Fellowships map to Emerging Leadership level 2, and Research Fellowships map to Leadership levels.

Due to differences in eligibility (according to years post-PhD) as shown above, the correlation is not perfect. But it serves the purpose of being able to compare as the NHMRC intended at least.

For the nitty-gritty details of the number crunching and visualisation techniques that went into the makings of this post, be sure to check out the post soon. If you’re simply here for the pretty pictures and insights, read on!

Key insights

Overall trends

At first glance, it appears as though the new investigator scheme has seen an injection of more money into the Fellowships portion of NHMRC funding. However, this funding includes more money per person at the upper tiers without a substantial increase in the number of applications funded. Moreover, the number of successfully funded applications and dollars was skewed toward the Leadership levels with an overall decline in the number of level 1 and 2 (Emerging Leader) applications funded.

The decline in the number of applications funded was matched by a substantial increase in the number of applications submitted, leading to a nosedive in the success rates particularly in the EL2 and L1 brackets. This increase in applications was thought to reflect the changes in eligibility structure meaning everyone had a go and often at levels far below what was appropriate for their research experience. The NHMRC is reported to be hopeful the number of applicants will decrease in the next round (thus artificially inflating the success rate).

Location, location, location!

With the conglomerate of research institutes, personnel and equipment in Melbourne, it has always been tough to beat in funding success. The same was true of this year, with Victoria the overwhelming leader in the number of awarded applications and second-highest success rate. In fact, Victoria received more than 45% of the awarded Fellowships in 2019.

The large number of applications originating in Victoria, coupled with their high success rate, suggests that not only is there a critical mass of outstanding researchers concentrated around the Melbourne biomedical hubs, but that they benefited immensely from the support processes in place in the lead up to submission. Hopefully, other institutes around the country can find value in their strategies for the following rounds.

Gauging the gender gap

Gender has always been a touchy topic when it comes to Fellowship funding in Australia, especially at the later stages of academia. There were concerted efforts made to target gender equality in the new scheme. However, at first glance, there was an enormous bias in the total number and dollars awarded. In fact, this disparity is the worst that the Fellowships scheme has seen in the last five years.

If we dig a little deeper, it becomes clear that this skew is due mainly to biases in the upper tier of the scheme. In fact, at the first and second tiers (level 1 and 2), there has been progress toward equality and, in some cases, even over-representation of women for the last five years. However, the successful males outnumber females two to one at the highest tier (level 3).

Two to one. The new scheme, if anything, has made this worse with the proportion of awards for women the lowest it has been since 2015. This points toward a systemic issue with how relative to opportunity is assessed and the lack of support for women entering the upper echelons of academia that is still ingrained in the research culture in Australia. Moreover, the extended 5-year term of these awards means that these differences will permeate University faculty for many years to come.

Titles and track records

As a general benchmark, academic titles say something about a researcher’s seniority. Considering the distribution of titles among successful awardees, there is a clear trend toward more and more senior researchers finding success at lower levels of the Fellowship scheme. For example, Associate Professors have taken a share of the level 1 funding for the last two years and for the first time, there was an Emeritus Professor awarded level 3 funding in 2019.

Similar trends can be seen in the track record of successful awardees, especially their publication history. While this is imperfect due to author name mismatches, overall the median number of publications for level 2 awardees has held steady around 50. In contrast, level 3 saw a sharp increase this year for the first time. The median number of publications for level 1 awardees has also steadily increased, meaning that to be competitive ECRs now need on average twice as many publications as they did 5 years ago.

With the revamp of funding levels and removal of specific ‘years-post-PhD’ ranges for level 1 and 2, this was always a concern. While I have (many, many) issues with using the years-post-PhD award as a ruler to measure relative success, at the bare minimum I do believe this distinction helped stratify junior researchers in the eyes of reviewers and assisted their assessment relative to opportunity. Unfortunately, the lack of boundaries this year left many researchers unsure of the appropriate level of funding they should apply for and moreover allowed many to take advantage of the lower levels in the scheme. This placed a large responsibility on reviewers to fairly evaluate an individuals trajectory against others with up to 10 years longer in research. A big ask!

Trendy topics

With every application, researchers include up to five keyword phrases describing the focus of their proposed research. By looking at the most popular keywords, I wanted to understand the research themes attracting the most funding and potentially consider how this has evolved over the last few years.

2015 keywords

2019 keywords

Interestingly, the top five keywords for the previous five years have typically been some iteration of health, disease, biology and cancer. While these seem very general, reading between the lines reveals a transition from ‘disease’-driven research to ‘health’-centric. Interestingly, epidemiology has emerged as a prominent focus this year. Cancer research has also held a steady proportion of funded applications, suggesting an area of high priority either among reviewers or impressive researchers embedded in this field.

What is unclear from these trends is the type of research being funded in these proposals. This is captured in the NHMRC reporting process as ‘broad research themes’. Traditionally, fundamental (Basic) research has held a large share of the total funding. However, the last five years have seen a steady decline in this proportion and a corresponding increase in the more translational themes.

In particular, clinical medicine and science enjoyed a sizeable bump in the proportion of funding awarded such that it has almost reached parody with basic science. This likely stems from the strong emphasis on ‘research impact’ that permeates all aspects of the new scheme, and at face value is not terribly alarming. However, our translational research must be underpinned by quality fundamental understanding and our ability to fund this type of research from the NHMRC scheme appears to be questionable in the future.

What does this mean for science, and ECRs, in Australia?

Overall, there has been a shift toward more senior and established researchers in all three levels of award. This is not merely a consequence of the new scheme, but has definitely been accentuated by it. This is likely reflective of the desire to invest in researchers who can demonstrate their previous impact has a direct and immediate public benefit.

This is also reflected in the share of the pie gobbled up by each of the four broad research areas, where Clinical and Medical Science has seen a steady increase at the expense of Basic Science.

While I made every effort to take a comprehensive snapshot of the available awardee data, these insights were limited in part by fragmentation of the data. The raw data provided by the NHMRC includes summary totals e.g. by gender or by state, but often the per-applicant information, due to obvious privacy reasons, is not available.

Some of the missing data, such as the years-post-PhD for successful applicants, could, in theory, be provided anonymously and would provide tremendous insight for potential applicants. At this stage, the closest proxy for years post-PhD is the mean age of awardees (although this as a measure is complicated by relative to opportunity). This year the mean age for level 1 awardees increased from 35 in 2018 to 37, agreeing with the overall sentiment of increasing seniority among successful applicants. With the restructuring in 2019, the NHMRC has all but done away with the ECR funding dedicated for those entering the postdoctoral workforce and require us instead to relying on the provision of project funding by senior researchers for many years before being deemed worthy and ‘impactful’.

There have been a number of statements released by associations commenting on this and other perceived failures of the new scheme, and suggesting changes to overcome these issues. For example, the released a host of recommendations aimed at alleviating many of the pain points ranging from the application structure to review processes. However, the short turnaround time (given applications for the next round open tomorrow and close in a little under two months) means that these recommendations are extremely unlikely to be implemented until next year. Moreover, this is a general and of research funding schemes world-wide. At this point, like so many other ECRs in my position, it is now time for me to think about whether my time, energy and effort are best placed in the hands of the NHMRC, other Australian funding schemes or - like so many in my position - whether I should instead focus on opportunities abroad. In the spirit of data-driven decision making, hopefully these insights have helped guide your thoughts as they have mine.

Resources

The original data was sourced from the
For more on the initial guidelines provided during the scheme restructure, check out the
Author track record information, including publication number and field-weighted citation impact, were collected from . If you are considering an application in the upcoming round, it’s a great idea to benchmark yourself against previous successful applicants.
For more info on the specific number crunching and data visualisation techniques used here, don’t forget to keep an eye out for my post.

Are you thinking of applying in the next round of Investigator Grants? Did any of these stats surprise you, or were they helpful in your decision of whether or not to apply in the next round? Head over to the , or let me know on .

Image credits: inspecting gears with magnifying glass | @ pluyer via

FASEB Protein Aggregation Conference 2019

Sun, 30 Jun 2019 04:29:41 +0000

After a science career spanning a decade without having attended an international conference, I have been fortunate enough this year to speak at not one but two! What follows is a not-so-brief rundown of my second international conference, what I learnt along the way and where I am hoping to take these lessons.

The benefits of a niche, narrow-focused conference

From the very first keynote speaker (shout out to Judith Frydman - what a powerhouse for proteostasis research), it was clear to me that this was going to be different to almost any other conference I have attended in the past. This conference (and in fact, the same is true for most FASEB themes) was very targeted around a single area of biology (protein aggregation), meaning that the talks were all very focused and relevant for all attendees. Indeed, the tight-knit and collaborative nature of this community was exemplified by the fact that each speakers acknowledgement slides listed at least one - normally many - other attendees.

It was so refreshing and heartening to see a dedicated community of brilliant researchers converge around this problem with a singular view to solving the puzzle of disease-associated aggregation. As well as this, there was a broad range of techniques on display and I felt that I left with a fantastic cross-section of the breadth of work being done in the field, both for pathogenic and functional amyloid aggregation, ranging from single-molecule through structural, cellular and whole-organism studies right up to clinical trials. Importantly, plenty of researchers presented unpublished data (presumably due to the diminished need for an extensive background in this audience, who are likely to have seen the speakers published works) that I would otherwise not have seen for many more months/years if the paper is held up during publication.

For me personally, this conference represented the intersection of my PhD work (centred on aggregation of a specific protein) and my current postdoctoral work (focusing more broadly on proteostasis and its role in disease-associated protein aggregation). So much has happened in the field since my PhD and it was pure bliss getting to nerd-out surrounded by like-minded people. I was surprised more than once at the new connections my brain was able to find in this setting. I found that by listening to many perspectives/methods targetting similar biology, it was easier to start to integrate those complex ideas rather than reading the papers in isolation. Aside from this, for the junior attendees like myself this conference made for a fantastic job market, with many lab heads in our field advertising positions.

Lessons learnt

A good and engaging speaker is one who is in tune with the audience, including their level of engagement, and who respects the time of the audience by sticking to their allocated slot.
Aim to engage. In a small group such as this, you will inevitably run into many of the high-profile speakers - maybe even at the breakfast table! - so it is essential to have attended and engaged with their talk. Bonus points for devising an intelligent question to follow up on their presented material!
The “comment and a question” audience member will always elicit a collective groan - don’t be this person!
Conference organisation is no small feat - but inevitably the strength of the organisation team will impact on the general experience. In this case, a lack of confirmed program less than a week out from the conference was not a good sign. Missteps in the organisation led to the chaotic herding of humans to food and coffee breaks and program potluck ensued when the speaking slots were revised on day one of the conference.
Location, location, location: Snowmass was an incredible conference location. A small ski village easing into the break between winter ski and summer hiking seasons, there was plenty of sunshine and a brisk breeze all set in front of a stunning snow-capped mountainous backdrop. A huge highlight of the conference was the relative isolation which, while difficult to travel to and from, heightened the sense of community and connectivity between attendees. Spending time immersed in the location will strengthen your connection to that conference. Snowmass made this particularly easy, with plenty of Springtime hikes, walks and sunshine on display.

The who, what, when and where of woeful wifi - an outstandingly woeful conference internet connection elicited plenty of complaints throughout the week. However, I did feel was more engaged with talks that I might not have otherwise prioritised, as it was much more difficult to multitask with attention-sucking admin jobs like email. While sticking almost 100 researchers in a room for large swaths of the day that does not have reliable internet is probably a recipe for disaster, it certainly supports the age-old adage of ‘unplugging’ during seminars/conferences to be emersed in the research at hand.
Chairing is caring - an experienced chair who takes control of a session, including speaker introductions and managing question time, can have a profound impact on the speakers and attendees. It is not a job that should be taken lightly. It is worthwhile paying attention next time you have the chance to observe an adept chairperson, taking note of the often unseen acts that contribute to a flawless, inclusive and positive conference session.
The diversity debate among question askers - it struck me how often the same group of 5 - 10 people in a room of ten times that many were always the ones to ask questions. I have never taken to the microphone at a conference to ask a question of the speaker. Not due to lack of ideas - I will often have a list of question ready and waiting to be addressed - but I always lack courage in a room filled with ’experts’ and my imposter syndrome keeps my butt glued to the seat. Is this maintained as some kind of PI-ready test you have to pass? Throughout this conference, I ruminated on the idea of how to engage people other than those that are brave enough to take to the microphone - there are plenty of free crowdsourcing options out there ( and to name a few), and yet I have not seen a single conference where this is adopted. I am keeping a keen eye open for an opportunity to put this inclusivity initiative into action.
By far the biggest take home from this conference was that everything which seems so significant before leaving for the conference (poster prep, student meetings, experiments, slides, …) will no longer be so important once you arrive, and will be overcome by things like remembering faces of people you meet, feeling comfortable in a room of strangers, testing the confines of your comfort zone and nailing your two-minute “who I am” pitch. I am still working on perfecting these aspects of conference attendance!

Personal perspectives

“Growing a pair” is a lifelong process: it is important to make the most of opportunities at a conference (which can often be once-in-a-lifetime combinations of people, place and perspectives) while understanding and appreciating your limits.
Finding your people and your place: while engaging with diverse people is a key goal of attending any conference, recognising that you need smaller groups and its OK to need more relaxed time (e.g. spending time with small group of colleagues for drinks at a local bar instead of the crowded networking events.

The psychology of ideas: you know that feeling when your idea is discussed during a meeting, and the academic goes on to believe it was theirs? For the first time ever, a senior academic articulated to me their inability to discern where an idea comes from, and it was enlightening. In contrast to my previous reactions, this wisened academic encouraged me (and the other early career researchers present) to hold firm when this happens and to realise that it is most often without malice but simply a product of the multitude of ideas and meetings senior researchers attend every day.
The importance of a mentor in science: it’s no secret. In fact, any time I have spoken to an academic about their career path and trajectory they speak constantly about the different mentors that smoothed their journey. But this conference, I spent a bit of time reflecting on the importance of proactively approaching search for good mentor-mentee relationships. Having mentors that enter your career organically is important, but you should also identify and target strategic additions to your ’team’ of mentors.
Who am I? Every successful and prominent researcher to take the stage at this conference began with “My lab works on…”. It is important to define this early on, and I am very aware of this hole in my current career focus.
The value of contemplation: Conferences have been one of the few times this year that I have taken the chance to sit and think - really think - about science (and life and decisions). While I would like to bring more of this deep contemplation to my every-day science, I am learning to accept and expect these events to be heightened moments of reflection and embrace the soul-searching mood!
Trading hats: with a few days set aside before and after the conference for travel, it was incredible to put on my long-lost tourist hat and enjoy the sights, sounds, smells and sensations of being in a new country. This experience reminded me of how lucky I am to have the opportunity to do this as an academic, and that I should more often take time to reflect on that privilege.

Overall, this conference was a tour-de-force of world-leading experts and cutting-edge research, and included several abstract-selected talks from ECRs (including myself!) that together comprised a diverse and wellbalanced program in a stunning location. Were you in Snowmass this June? Get in touch via and let me know what you thought of the FASEB Protein Aggregation Conference!

Banner image credits:

EMBL Proteomics in Health and Disease Mechanisms 2019

Sun, 24 Mar 2019 07:19:06 +0000

Last year I had the privilege and pleasure to attend (and present at) four scientific conferences. This year is shaping up to be just as wonderful, as I have been lucky enough to attend two conferences is as many months, marking the start of what I hope to be a productive year ahead. Here is a little about my recent European adventures, including my first oral presentation at an international conference.

Conference details:

Title:

Date: 7th - 9th March 2019

Location: Heidelberg, Germany

Overview:

Focused on the application of proteomics to cell biology and unraveling disease mechanisms by addressing conceptually novel ways to study long-standing questions in these fields. As most proteomics-based conferences tend to focus on analytical chemistry, the selection of biological topics is usually uneven. Therefore, this unique conference aims to showcase biology applications and build bridges to the disciplines where the technology’s promise is still not nearly fully realised.

There’s a first time for everything!

This was my first truly international conference. What do I mean by that? I have attended and presented at several Australian national conferences consisting of international speakers, but was yet to have travelled overseas to visit a conference in another country. Unfortunately, our isolation makes such an undertaking on a student or starting post-doctoral salary near impossible. In this case, I had been madly applying for every pot of travel funding I could find for the last year, and in a fantastic “it-never-rains-but-it-pours” moment I received all three of the grants I applied for! This meant I was able not only to travel halfway around the world and attend a pre-eminent conference in my field, I could also afford to visit some long-term collaborators for a week afterwards. All together, the two weeks of travel were almost entirely covered and this meant that instead of being consumed with the cost of my every move I could actually focus on the science.

Overall scientific programme and conference feel

Not only did I get to hear about all the amazing developments at the forefront of proteomics research worldwide, I also got to showcase some of my work to leaders in the field. This was an incredible opportunity, and while I was a little disappointed with my talk (owing to sub-optimal preparation and a large dose of nerves), I received overall positive feedback. As well as this, there was so many advances in techniques and biological understanding that I would have never come across on my own, at least not within the next 12 months while the papers are being sucked down the peer-review black hole!

As well as a stunning program, I feel I must give a bonus shout out to the EMBL organising team. Everything ran smoothly, was well organised and timed, and was superbly catered. There was also a small enough number of participants and a well-balanced program between students, post-doctoral researchers, principle investigators and moguls of the field. A conference I would highly recommend to anyone interested in the biological applications of advanced proteomics techniques.

So conferences are just an excuse to travel?

Conferences are the life-blood of academic knowledge sharing. You might think the enormous volume of published literature would be the best source of the up-to-date goings-on of the science world, but sadly in most circumstances you’d be wrong.

I have written before about the importance of conferences, particularly for those of us a little isolated outside the major American and European science hubs. This is because these conferences are essential for establishing and maintaining connections with colleagues, and for hearing about the cutting edge research being done in your field all over the world. As I alluded to above, unfortunately by the time most manuscripts have made it through the academic publishing process, six to twelve months have past (sometimes more) and there are more new and exciting developments already happening (with the advent of preprint servers such as BioRxiv this will hopefully change, but more on that in a later post).

For these reasons, conference attendance in particular for early-career researchers, is about so much more than the travel. Sure, it helps if the places you are visiting are enticing and if you can spare a few days afterward to explore, but the invaluable aspects of conference attendance always take precedence.

Lessons learnt

As my first international meeting, I learnt some new lessons about attending (and making the most of) conferences abroad.

1. Multiply your typical organisation time by at least double. International travel, in addition to conference attendance and accommodation, requires a significant investment of time and energy to plan and book a reasonable itinerary.

2. Departure day is not that far away. I realised after madly rushing to finish my slides on the 14 h flight from Australia to my stopover, that I had perhaps underestimated how quickly my departure date would approach. I was so focused on tackling the seemingly all-so-important last minute experiments and meeting with my students to plan their activities while I was away, that the very reason for my trip got pushed to the side. The result was a less-than-flattering performance during my presentation, and a general feeling of exhaustion throughout the conference which dampened my social spirit. Consequently, I did not proactively initiate many interactions with other attendees, and therefore failed to make as many useful contacts as I otherwise could have.

3. Do your research, researcher! This mostly relates to scoping out the program beforehand. Sure, reading the headline speakers you should be able to identify any leaders that would be good to hear from. But more than this - look over the abstracts, and pinpoint those which are relevant, interesting or potentially useful. To assist this process, concurrently search the presenter in PubMed to get a handle on their other research. Unfortunately, an abstract may not do justice to a programme of scientific discovery, however reading the most recent/most cited articles will help you highlight not-to-miss talks. In addition, I got caught out this conference by an invited speaker whose most recent papers have been instrumental in my project design. Unfortunately, I recognised the first author’s name, and not the speaker (who was senior author on the papers in question) and therefore missed an initial opportunity to discuss this work in depth with the driving principle investigator. Having then done my homework, I was able to make this crucial connection.

4. There will be other conferences, but this is a once-in-a-lifetime experience. Sure, there will be uncomfortable moments, especially attending a conference in a foreign country surrounded by unfamiliar languages and faces. But the best in life happens outside your comfort zone. Unfortunately, it took me a significant portion of the short three-day meeting to push my comfortable boundaries, and after the first two days I left feeling as though I had not taken enough advantage of the opportunities a small meeting with superstars-of-the-field presents. I was disappointed in the impression I made over these two days due to my lack of will power to engage in the social activities, and this was compounded by the feeling of responsibility to those who had funded my trip (including the conference organisers, with a very generous stipend). Ultimately, by the end of the conference, I gathered the seeds of a few meaningful connections to chase up by email - and the very important lesson to make more of these meetings in person in future.

Final thoughts

There are plenty of downsides to science (hellloo no job security, poor work-life balance etc) and travelling (long-haul flights, little sleep, $$$) - but conferences provide a great opportunity to combine the best of both. I would thoroughly recommend this conference, or any in the series of , for early-career researchers looking for an excuse to visit Europe and beyond.

Have you attended any other international conferences or EMBL events you can recommend? Find me on or head over to the to tell me more!

Many thanks to the generous funding provided by the Bio21 Institute Post-doctoral Fellows Travel Grant, the University of Melbourne Faculty of Dentistry, Medicine and Health Early-career Researcher Travel Award and the EMBL Corporate Partnership Programme Travel Grant. Without these initiatives, this travel would not have been possible and I am so very grateful for the opportunities provided by these funds both at the conference and beyond.

Image credits: EMBL Conference logo sourced

Quick Recap: PyLadies Melbourne Event

Tue, 31 Jul 2018 11:24:05 +0000

Locating the labyrinth a nd meeting the meetup For a few months, I had been working on the courage to check out one of the many coding-related groups held all across Melbourne each month. There are the meetups, various networking events and more data science groups than I could possibly list here (if any of these peaks your interest, check out the meetup list ). Still, as a scientist-turned-programmer (and a shy one at that) I wasn’t too quick to jump in the deep end with a roomful of people who of course I assume know everything there is to know about programming. Eventually, an email popped into my inbox with details for an upcoming centered around a tool I had been using (and hating) almost daily, and finally, I thought, “This is it. It’s now or never”. So, a cold Melbourne Monday night I bundled up my backpack and headed into the city after a long day at work.

After a tricky start (getting into locked business buildings in the heart of the Melbourne CBD is not my strong suite - mastermind criminal I am not!), I finally made it to a table jam-packed with Souvas accompanied by a fridge full of beer and cider (or apple juice poppers if that’s what you’re into). I was one of the last to arrive, so I quietly slunk in the back and collected some food before introducing myself to the orchestrator of the event. Not long after a quick round of “What’s your name, what do you do…”, we were bundled through to a second room where there was a bunch of tables and chairs set up around a projector.

For the next 90 minutes, enthralled and entertained with her tales learning python’s premier plotting library, matplotlib. I won’t go too much into the finer details of her talk - you can check it out . But, I will tell you a little about Ash and why her talk being my first foray into python meetups was so important. A masters student come research assistant, Ash is a bench-trained scientist with a flair for uncovering transcriptional signatures of immune genes in cancer. She came into python as the only scientist in her lab using this language and has built analysis pipelines for her work from the ground up. Coming into python as a scientist was definitely something I could relate to! Ash was brutally honest about how hard she found it at times to navigate the various Matplotlib interfaces. She unashamedly admitted how easy it was to spend hours ‘prettifying’ your graphs. And most importantly for me, she had a room full of fellow pythonistas, mostly software engineers and data scientists, nodding along. It was unbelievably reassuring to hear that I wasn’t alone in my experiences of matplotlib-induced pain. On top of that, having someone methodically explain the basic concepts, the tricky syntax and the bizarre labeling conventions was so helpful for crystallising the knowledge I had slowly accumulated over the last year or two since starting to use matplotlib more regularly. I even learned a few new tricks (aspect=‘auto’ anyone??).

I know it may seem like I’m gushing (and maybe I am, a little) but it truly was a revelation to me that scientists could have something so useful and relevant to contribute to what (on the surface) seemed like a simple conversation for those ‘in the know’. The PyLadies are an incredibly welcoming bunch, and I can’t wait for next month to ‘meetup’ with them again.

The nitty gritty When: Third Monday of each month Where: Melbourne CBD Who: Anyone identifying as female who is interested in python. What: The presenters and topics vary by month, so for all the details make sure to check out the PyLadies meetup page.

Note: The details I’ve included here are for the . If this is not near you, don’t dismay - there are PyLadies groups all over the world and most likely one near you! There are even remote PyLadies groups that regularly post talks online if this sounds more like your jam head to check it out.

Python not your thing? There are so, so many different groups on , I am sure you will find something that takes your fancy!

Resources If you’re in a world of matplotlib pain, here are a few of my favourite resources that (along with Ash’s talk) really help to lay out ground rules and will hopefully give you a fighting chance:

the nomadic scientist: blessing or curse?

Thu, 05 Apr 2018 10:36:32 +0000

From the very beginning of my undergraduate degree, I knew that I wanted to pursue research overseas. Not so much a permanent relocation, but I was very keen to leverage the international nature of science to see the world. I secured a post-graduate position with a group leader who was open and supportive of this goal, and was instrumental in helping me go abroad during my PhD research. What followed was a whirlwind trip to Cambridge, UK, where I worked on acquiring a new technique to add to my developing skills arsenal. Despite the short stint, it was hands down the most personally and professionally life changing experience.

This is not to say that my home institute isn’t producing to good science - it is - but through this experience I was immersed in a city bursting at the seams with passionate experts, cutting-edge research and world-leading techniques. To say I fell in love would be an understatement. The cohesiveness and intertwined networks I observed whilst there were an incredible, eyeopening window into the collaboration that comes from bringing together world-leading experts from a broad range of disciplines in a melting pot dedicated to the pursuit of knowledge.

After returning to Australia, I worked towards the holy grail - thesis submission - and dreamed of the postdoctoral jobs I could chase internationally. One year on I am still here, and in a position I am thoroughly enjoying, but you better believe I still have my eye on an overseas position in the next 5 years. I do wholeheartedly believe that a diverse research training period is a critical foundation for a well rounded researcher, giving context and cultivating understanding of the abundant theories and approaches one can take to answer the big scientific questions. Diverse experiences offer the chance to explore the problem at hand from a new perspective, leading to unique insight.

And as excited as I still am about all the places science could take me in the next few chapters, my extra-continental daydreams have been tainted with an air of urgency of late. I am beginning to feel as though, with the current funding climate, the only way I am going to get a foot in the door is to do my time in a country where the pay is less, the work-life balance a little more unbalanced and my family a little(lot) further away. Even worse, I am acutely aware that in this situation I am the privileged one. Assuming I am lucky enough the secure a position in a good lab group in my area of research, I have very few restrictions or barriers to relocation. Sure, money is always an issue. And there might be a few personal hiccups (my partner is not infected with my incurable case of wanderlust), but I am (relatively) young, without kids and with no significant financial constraints (other than the misguided hope to someday get on the property ladder).

Many of my colleagues, and friends, do not enjoy the same level of flexibility.

And so, I suppose this post is more about what you think - is it possible to progress in the Australian scientific research landscape without being a nomad, at least for a little while? And what effect does this have on the diversity retained in the upper echelons of the academic institutions?

Lorne Conference Series 2018

Sun, 11 Feb 2018 05:31:58 +0000

At this point, I think I have written more about conferences than anything else. I am sure you are thinking that is all scientists do - Don’t be fooled! I have been incredibly fortunate to get to so many conferences in the last few months, culminating in two iconic fixtures in the Australian protein science conference circuit - Lorne Proteomics and Lorne Protein Structure and Function. I wont belabour the point about how important or valuable these conferences are (at this point, it gets kind of redundant!), but I will give a quick overview of my experience of the Lorne Meetings 2018.

First, it is important to understand the origins of the Lorne meetings. Starting out in the 70’s as a humble symposia, the Protein Structure and Function Meeting this year celebrated it’s 43rd installment. It is now at the centre of five consecutive meetings that run throughout February in the lovely beach town of Lorne, Victoria, covering Proteomics, Proteins, Genomes, Cancer and Immunology. I have been to a few of the Proteins meetings throughout my PhD, but this is the first time that I have attended two of the Lorne meetings back to back. It gave me a unique perspective on the similarities and differences of each meeting, and I benefited from each in wildly different ways.

A nice feature of the Lorne meetings is that the experience starts during the transit to Lorne. This year I traveled with one of my supervisors, and it was a great opportunity to have some one-on-one time. If you ever get the chance to travel with your academic mentors, I highly recommend grabbing it with both hands! It is through these conversations that you can get to know the person behind the science, and the politics behind the academic. For me, these conversations have been a highlight over the years, and this was no exception.

The first in my lineup was Lorne Proteomics. Given proteomics a very new skill to me, this was a great opportunity to get up-to-date knowledge from leaders in the field and help cement my growing understanding of best proteomic practices. I felt very alone and new to this crowd, with only one or two familiar faces in 240 delegates. However, I was lucky to be a speaker selected from abstract (a fancy way of saying I applied with a description of my research, and they chose me as one of the ~60 presenters). This was a true treat, as it was a great way to introduce myself and my work to a completely new network of scientists. I got some great feedback and a brand new approach to my project. What struck me most about this conference was the diversity of science that was covered in the talks. Being primarily a technique based conference (as opposed to a biological theme as with the Proteins meeting), there were marine biologists, physiologists, ‘method’ologists (mass spectrometry, crystallography, electron microscopy), molecular biologists, statisticians and mathematicians. It was a great overview of the scope of disciplines in which proteomics and associated techniques are both indispensable and actively developed.

An interesting side-note to this conference was the inclusion of the Annual General Meeting for the Australasian Society of Proteomics. This was my first foray into Society politics and management. It was a really great opportunity to observe the inner workings of the society and see where I could potentially get involved in the future. There were rumblings of an ECR-led program for Lorne Proteomics 2020, so stay tuned!

Barely a few hours after the close of the Proteomics meeting, the Proteins delegates descended on Lorne. The faces were more familiar and, for someone who enjoys the sensation of routine, everything felt a little more like ‘home’. The first night featured one of my favourite sessions - the Leach lecture, in which an emminent Australian Protein Scientist is awarded the lecture and intertwines personal experience with scientific detail. This year’s lecture was given by Ray Norton, and he did not disappoint.

Ray Norton on his journey, quoting John Lennon (or more accurately Readers Digest!)

“Life’s what happens when you’re busy making plans”

— Dezerae Cox (@dezeraecox)

Other notable sessions included the Student & Invited Speaker lunch, where I was a ‘facilitator’ (my job was to help stimulate conversation across the table). As well as the great opportunity students had to interact with our international visitors, there were two keynote speakers. First, Liz Miller gave a great summary of her science journey - how she had landed in her first post-doc, managed to coordinate two academic careers across the globe, and how she had taken advantage of the often serendipitous nature of science. Her take home message was planning moves in science takes time, so start looking and thinking about it early. This was echoed by Nobel Laureate Richard Henderson, whose take-home message was to do almost as much research into the paths you can take, and the places you can go, as actual science itself. I think, in our current scientific and political climate, that these messages could not be more timely for students to hear from leaders in our field.

Last but not least, I had the chance to catch up one-on-one with two of the international speakers. Building on my confidence from the Proteostais and Disease Symposium, I took this opportunity to get their input on my current project, their thoughts on my career goals and their advice on moving forward over the next few years. I am truly amazed, and incredibly grateful, for the generosity of experienced researchers in offering their mentorship to me as a young Early-Career Researcher - it turns out that sometimes all you have to do is ask.

It goes without saying, that if you ever have the chance to get to one of the Lorne Conferences you wont be disappointed. Hopefully I’ll see you there next year!

my attempt to pay it forward: MicroMentorHQ

Wed, 17 Jan 2018 04:03:50 +0000

I should start by acknowledging that I have always considered myself very lucky to be where I am. I am doing what I love (Science) in a (mostly) brilliant and (definitely) beautiful country, and I am conscious of the insane priviledge this is. This feeling of being priviledged has been a common thread throughout my secondary, teriary and graduate education, and continues now in my current postdoctoral position. I now find myself in one of (if not the) the most vibrant centers for science in the country. I am surrounded by people who are both good at their job, and emmensely passionate about it the mechanics of doing it well - how to be better at the technical science, but also how to progress in academia and how to leave the ivory tower a better place than when they found it.

Where before I was surrounded mostly by students and had met only a handful of postdocs during my PhD, I am surrounded for the first time by a critical mass of other post-docs. Suddenly, I have access to this wealth of resources and networks - both emotionally supportive and practical advice on the best ways to survive the post-doc squeeze (link here to Maggie’s STEM info with the squeeeze point diagram) and make it to the top of that ivory tower. One of the points that kept coming up again and again is the importance of mentoring and sponsorship - both in the traditional sense of experience mentor to inexperienced mentee, but also peer mentoring to foster emotional wellbeing.

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During one of our frequent trips home last year, this topic came up in conversation with a few friends of mine from my home institute, one a current post-doc and one a final year PhD student. It saddened me to realise just how lacking these networks were for them. Despite being well prepared in the technical sense for the next career move (they both do excellent research), we all felt a little ‘out of the loop’ when it came to the trickle-down knowledge that can only come from those who’ve come before you. Some of this is mitigated by twitter (the scientific twitter community really is quite incredible), however engaging with Twitter as a platform was another thing that had not ’trickled down’ to these friends.

I resolved that this was my chance to pay it forward - to take what I was exposed to, and the lessons I was learning, and pass it along to late-stage students and postdocs. And so, MicroMentorHQ was born. First and foremost, I wanted the group to be a peer mentoring community for women in science, particularly Early-Mid Career Researchers. The inherent idea was that we all have valuable experiences and by connecting us wherever we may be in the world and at whatever career stage we are at, hopefully we can more easily elevate one another in the world of science. The current funding climate, and the other cruelties of doing science, also means that we need to get better at sharing opportunities and celebrating success, and I hoped to build a network that would encompass all of these ideas.

The experience, it’s is current form, I think is somewhat like a lunchroom with separate tables (or message boards) for different conversations. There is a place to introduce new members, where I hope to post bio’s to enable everyone to get to know each other and maybe even get the collaborative juices flowing. There is a message board specifically to curate any funding opportunities, including fellowships, grants, travel funds and awards. It occasionally includes reminders for upcoming deadlines and is a great place to share helpful advice for the application process. There is a board for science life i.e. when someone is reading something interesting, learning a new technique, celebrating papers published or grants won. Most importantly, there is a board from Human Life - where someone can ask for advice, tell a story or post photos of their kids (or dogs or cats). In science I find it all to easy to forget that we are all human beings and I honestly believe this needs to become a bigger part of the conversation.

Fast-forward two and a half months, and we have ten members. One of my main personal goals for 2018 is to grow this community, to help connect those in a similar situation such that they too can access all the benefits of being in a rapdily evolving scientific research hub. It may work, it may not, but I feel it is my responsibility to at least try to pass along the great fortune I have enjoyed so far.

If you’d like to get involved, have any suggestions or comments please get in touch - I’d love to hear from you!