Tag Archives: Decisions

The 10-step program to quitting astronomy

I left astronomy formally 18 months ago and recently finished up a computational modelling job in public health. With a little bit of time and perspective I now present to you my 10-step Program to Quitting Astronomy. Or any line of work. I’m not arguing that you *should* leave. This is simply about the process. Some of the details are specific to my aims, but I’m also incorporating a range of advice from my friends and colleagues, who each have their own unique goals. These steps don’t have to happen in exactly this order, but you’ll want or need to do most of these at some point. Good luck!

The 10-step program

  1. Acknowledge your feelings
  2. Identify your skills and interests
  3. Decide what to do next
  4. Find a mentor
  5. Go public
  6. Form a study group
  7. Re-train and re-brand
  8. Transition
  9. Settle in
  10. Mentor others

Let’s break these down.

1.
So: you’re thinking about quitting astronomy. Why are you considering leaving? Are the problems specific to the job? Or a consequence of unusual circumstances? Could they exist in all workplaces? What future do you picture if you continue? What do you expect if you leave? What are the risks of leaving? What are the risks of staying? What are you afraid of? Do some honest soul-searching; talk to friends; read some quit-lit if you like. I had never planned to leave, so I struggled and this stage took me a whole year. At the end of the day, you might decide to stay. That’s OK. But your mental health is your health, so make that a priority whatever you decide.

2.
If you make the decision to leave, then recognising your own skills and interests is crucial, especially when you come to re-branding (see Step 7). Make a mental list of intellectual interests and priorities (incl. workplace environment, autonomy, opportunity for progression, big picture, salary & benefits, flexibility & stability, family & relationships). Which of these are dealbreakers? My original list had astronomy near the top, and I had to gently but purposely delete it so that I could acknowledge its existence but then turn my attention to everything else.

3.
Decide what to do next *generally* speaking, both in terms of your career and other life choices (based on Step 2). Take every opportunity to hear from friends and acquaintances outside your regular professional sphere about what they do and who they work with. Ask whether they hire people with your background and skills. My first resource was the JobsForAstronomers website, which – back in 2012 – introduced me to the now famous Insight Data Science Fellowship. Insight has since spawned several other satellite initiatives and similar data science programs are popping up everywhere. At that point, however, what mattered wasn’t the programs themselves, but rather realising that my PhD would really be useful and valued elsewhere, that I wouldn’t be wasting my achievements, and that a path existed somewhere to mediate my transition. At first I was drawn to data-science, but later decided (after going back to Step 1) that I still wanted to do some academic work as an applied statistician but in a different discipline; now I sit somewhere in between.

4.
Seek out a mentor or three. Find ex-astronomers who are already working in a field you’re interested in joining (preferably people who you can relate to), ask them about what they do day-to-day, good companies/institutes to work with, where/how to look for jobs, and CV/application/interview tips. People are almost always willing to step up: advice is free and it’s flattering to be asked. In the last few years, a few Facebook groups have been formed to help with this. It’s OK to cold-call someone to ask for advice. I did.

5.
At some point you need to let people know your plans and where you’re looking to go. Partly for logistical reasons (so you can ask for reference letters) and partly for your own sanity (you can stop pretending that your sole purpose in life is to get a faculty job). As a bonus, once people know you’re looking for a job, they might just tell you about potential mentors and any openings they hear about. So go public with positivity. There’s no need to be defensive: you’ve made a (big) choice for valid reasons.
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Channel your inner career-transition spirit animal and explore new identities

6.
Find a few other people preparing to make a similar move and suggest that you form a study-group that doubles as a support-group. I’ve met these people either in my own department or at astro-conferences (these days people discuss post-astro careers at every single event; thankfully this is no longer a taboo subject). You can swap tips and discuss all the practicalities of steps 7 & 8. You will find out about twice as many job opportunities. Most importantly, you will not be alone in this.

7.
Re-training is simple; we do it all the time, like reading up for new projects or teaching ourselves new programming languages. But re-branding feels like a bit of a dirty word for a researcher. The fact is we’ve always been one-person companies: creating a product, marketing, consulting, HR, all wrapped up in a human package. Re-branding is simply about consciously influencing your potential professional community’s perception of you, communicating your expertise, what values you stand for, and ultimately if and where you would fit in with their team. Both re-training and re-branding could involve applying to fellowships and internships, completing MOOCs and kaggle-competitions, attending short courses & workshops, conferences & hackathons, meetups & career seminars, blogging demo-projects, and taking to social media.
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Also, take some decent professional photographs – you’ll need them.

8.
Beginning the transition involves a few things: job hunting, re-designing your CV, learning new interview skills, and time. Your mentors and support-study group will be crucial here so make the most of them. A good recruiter can do wonders, and networking is key. I found social-media to be very useful for serendipitous job ads, although I rely more on job-listing websites and newsletters. Interviews can be quite different to what you’re used to, so treat each one as a learning opportunity. Are companies reluctant to hire astronomers? I can’t speak for all companies, but I can tell you that to improve your chances you should avoid being seen as a risky hire: do your research, adapt to speak their language and understand their stakeholders’ needs. So… go out and score that job!
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Optional extra: transition between countries…

9.
Adjust and settle into your new job & new life. Get used to answering the question: “So, what do you do?”. I still almost always mention astronomy. No job is perfect, but sometimes it’s not until after we’ve had one job outside our previous career that we realise what we’d taken for granted. That said, nobody I know regrets their decision to leave. It’s OK to miss your research topic. I miss gravitational lensing terribly – the research, my colleagues, and the conferences. I still like to share major science news with my family, friends, and bus drivers. But why not get involved with other science disciplines? Why not the tech industries and start-ups? Why not help shape policy? Now that I’ve freed myself from the shackles of lifelong career goals, I have the opportunity to be part of any of it. I am also free, it turns out, to continue doing research astronomy as a hobby, at my own pace, on whatever I’m inclined to do.

10.
Congratulations! You’ve moved on – with some help. Now it’s time to pay it forward. From the moment you go public (step 5), you can expect requests for mentorship or at least a one-off chat. One year on, I was asked to speak on a panel to junior academics about alternative career paths (keep an eye on emails from your previous department and volunteer when you see calls for speakers). Your ability to help others transition will be useful for at least a few years, so go out and do your duty. Maybe write a blog about your experience.

Risk and rationality

I had the privilege of attending the 2016 Australian Academy of Science Theo Murphy High Flyers Think Tank in Canberra just recently. I’d only heard about it via a single tweet the day before applications were due, but with the topic of “An interdisciplinary approach to living in a risky world”, my response was: yes please.

We were also asked to choose our preferred topic for breakout-group discussion, and I got my obvious favourite, the technical theme of “Uncertainty, ignorance and partial knowledge”, which turned out to have some focus on decision theory. The session would chaired by Prof. Mark Colyvan, a professor of Philosophy at my alma mater, The University of Sydney, who had recently responded to Luke Barnes’s recent fine-tuning of the universe talk. Some of the recommended reading got me thinking about matters we didn’t get to cover (like how much I don’t like maximin), but I’ll discuss with Mark, and I’m sure I’ll blog about that later. In the meantime, our breakout group spent a couple of hours throwing around our thoughts and ideas and have begun to craft a report and recommendations for the Academy regarding decision-making and risk communication in the face of uncertainty.

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Wrap up from chair Prof Hugh Possingham

My fellow delegates were such interesting people from diverse backgrounds like health, maths, stats, philosophy, history, law, geology, ecology, microbiology etc, and absorbing ideas from these amazing people over the two days provided a complete mental recharge. It was like NYSF for grown-ups. Even the conference dinner speech by emergency doctor David Caldicott was so stimulating, leaving my laughing and crying, I’d dare say it was the “best event speech ever”.

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Slide from Prof Terry Speed’s talk at the AAS Think Tank

Actually one of the things I most enjoyed at the Think Tank was finding out people’s thoughts on rationality during tea break, as always. As it turns out, most people I spoke to (about this topic, sample size ~5) were adamant that people are at heart, irrational creatures. Only one person (besides myself) thought otherwise. I’ve been told I have to read Daniel Kahneman’s Thinking Fast and Slow to hear more arguments against the assumption of rationality. Apparently there are tests for this sort of thing…

Rational Agents

Recently I attended the second ever Bayesian Young Statisticians’ Meeting (BAYSM`14) in Vienna, which was a really stimulating experience, and something pretty new for me, being my first non-astronomy conference. I won a prize for my talk too, which was pretty sweet!

BAYSM`14 venue

Swanky BAYSM`14 venue at WU Vienna designed by architect Zaha Hadid

During the two-day overview of theory and a variety of applications by the newest people in the field (read about the highlights over at the blogs of Ewan Cameron and Christian Robert), we heard from a few Keynote Speakers including Chris Holmes. In his talk, he mentioned the world of rational decision makers as envisioned by Leonard J. Savage in his 1954/1972 tome The Foundations of Statistics (adding that on my ‘to read’ list), and went on to describe the application of a loss function and minimax to avoid worst-case scenarios. Minimax isn’t the only approach to decision-making; I think other approaches  are more relevant to our behaviour, as I’ll describe later.

“If you lived your life according to minimax, you’d never get out of bed” – C. Holmes

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We are all made of stats

Children are very good at science. They start with broad priors (anything is possible) and learn through collecting data (see picture below) what conclusions are supported best by the evidence. They experiment, make mistakes, and test the variations on a theme. They learn what is dangerous; they learn what is tasty; they learn how to speak.

Kids doing science

Kids doing science

Our responses to experiences are very similar to Bayesian reasoning. Take trust as an example. If some dudette off the street – let’s call her Margaret – were to recommend a movie, say Moon, we might not heed her words since we have no reason to think we’d have the same taste in movies as her, but if upon watching Moon we found that we quite enjoyed it – we’d be more likely to rely on Margaret’s next tip, say Wadjda. And if Wadjda was also to our liking, we’d probably trust Margaret’s advice when she suggests Fast & Furious 6 (oops). But that blunder would reduce our confidence in her next recommendation, etc. If we define our experience of the movie in binary terms such as “liked” and “disliked”, the situation resembles the classic coin-toss experiment in which one tries to determine if a coin is biased by flipping it many times.
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