What determines what I teach?

I very recently quit a teaching program that I have been part of for more than four years, to which I had a personal connection after all those years. Besides it being lucrative, it was also a program that was for a good part shaped by me and colleagues and which was fun and fulfilling to teach. Why quit, you might ask.

The program, consisting of modules for data scientists, analytics translators and managers/executives, was a collaboration between a consulting company, Ortec, and the Amsterdam Business School, a department of the University of Amsterdam that organizes a lot of executive education. The data scientist program was ruthlessly killed about a year ago, because of fierce competition from online platforms. Face-to-face education is more effective and in my opinion worthwhile, but if you can’t offer the right program for the right price, then it isn’t weird to decide not to. That so many people think you can learn such skills through watching a few videos and typing in two lines of code in a automatically checking code interpreter continues to amaze me and I bet we will see the devastating effects of this, now still junior, generation of Youtube data scientists in due time. But I digress.

The module for analytics translators is still alive and just these past few months I have still been teaching it. Fulfilling as always, I spent two half days in lecture rooms in hotels with a group of enthusiastic participants. The program this time was already rather different from what it had been before, and with the feedback of the current cohort, leadership decided to do another round of modifications.

Do not misunderstand me: continuously updating your educational offerings is what a good teacher does. Incorporating feedback from participants (or students) is crucial, as only they can properly judge whether your efforts help them reach their learning goals. One quote of the program director in the process made me scratch my head though:

I am just trying to design a program that I can sell.

Sure, selling your program is important, as otherwise there is no program. I get that. And for consulting companies (this program director is not with the consulting party in the collaboration) this may be the most or even only viable way of running business. I think, though, that people come to trusted educational institutions like universities for a different reason. A university does not design a curriculum for sales. It sets learning goals (which may well be (job-) market informed!) and then designs an educational pathway to best reach those goals. What people need to learn is determined by where they want to end up, not by what is a sexy set of courses that happens to be easily marketed.

Teachers are teaching what they teach for two reasons. Firstly, they want to convey knowledge and skills that they have to students who want to learn. They think about the right educational means to help the students gain the knowledge and master the skills. Secondly, they are specialists in the field in which they teach, which means that they understand like no other what is necessary to learn, before one can become a specialist in that field, too. Few astronomers truly enjoy the first-year linear algebra they need to master and rarely do psychologist enjoy their statistics classes in undergrad, but these happen to be crucial ingredients to grow into the field that you want to be part of.

Besides the communication between the various people in this program detoriating to levels that I didn’t want to accept anymore, the fact that the curriculum went from specialist-informed to marketing and sales opportunity informed was the straw that broke the camel’s back. I want to be a proud teacher. Proud teachers design a program that is the best they can do to help students reach meaningful goals. You are very welcome to set learning goals based on all kinds of arguments, including sales, but once the learning goals are set, you should trust the professional’s teaching experience to manufacture a great, fun, and helpful course or program. It will be better for everyone’s motivation.

PS. More on my new academic role soon, presumably!

New year? New career!

We’re at the start of 2023. It has almost become a habit for me to switch jobs about yearly, over the last few years. I have never intended it that way, but apparently I needed a few de-tours to find out where I wanted to go. I have not made it a secret that I regret quitting my astro career and I also have alluded to aspiring an academic career. My current job at the University of Amsterdam is adjacent to academia, and that was the whole reason I took it in the first place.

I have done fun projects, learned a lot about the ‘behind the scenes’ at universities and was a willingly active member in the interdisciplinary Data Science Center of the University of Amsterdam (UvA). Some things could have been better (“creating” demand for our work wasn’t overly successful, and support from IT for what we needed was consistently cut back to near zero budget), but I do not necessarily need to change jobs. With my leave, though, I have advised against replacing me by another Marcel. I think the money can be spent better, before another me would jump onto the Advanced Analytics bandwagon again at the UvA central administration. Thanks to all my colleagues at the UvA for an interesting and fun year and a half!

In the post that announced my current job, I described the road towards it, which included a second place in a race for an assistant professorship at a university medical center, shared with a computer science department. In a rather bizarre turn of events (details available off the record), I have eventually accepted an offer that is very comparable, and arguably even better than the position I was originally applying for. That means…

I’m proud to announce that as of Feb 1st, I’ll be an academic again!

I will be an assistant professor of data science in population health at the Leiden University Medical Center (LUMC) at their interdisciplinary campus in The Hague, where they also offer the Population Health Management MSc program.

I’m very excited to be giving a lot of serious education again, and to be doing research in a highly relevant field of science. I have very little network or track record in this field, so I expect to learn a whole lot! Keep an eye on this blog, I might be using it a bit more frequently again (no guarantees, though…). Here’s to a challenging, but fun 2023!

The bumpy road to academia’s side entrance

I have indicated already earlier on this blog that I miss academia, and that I wouldn’t mind moving back into an academic job. I have made some attempts recently and want to reflect on the process here. Spoiler alert: I’ll start a job at the University of Amsterdam very soon!

In my journey back into academic life I have also applied less successfully twice, and for reflection on that, it is probably useful to understand my boundary conditions:

  • I left my academic career in astrophysics now roughly 8 years ago and have not done any pure science since (at least not visibly).
  • I have few, too few papers from three years of postdoc. I left my postdoc position with no intention to go back, and therefore have just dropped all three first-author papers that were in the making on the spot. They were never and will never be published.
  • I am strongly geographically bound. I can commute, but I can not move. Hence, I am bound to local options.

I have spent these last 8 years on data science and gained a fair amount of experience in that field. All that experience is in applied work. I have not done any fundamental research on data science methodology, As an aside, I have of course learned a lot about software development and team work in companies of different sizes. I have seen the process of going from a Proof-of-Concept study to building actual products in a scalable, maintainable production environment (often in the cloud) up close, very close. Much of that experience could be very useful for academia. If I (and/or my collaborators) back then had worked with standards even remotely resembling what is common in industry, science would progress faster, it would suffer much less from reproducibility issues and it would be much easier to build and use science products for a large community of collaborators.

But I digress…. The first application for an assistant professorship connected closely to some of the work I have done in my first data science job. I spent 5,5 years at a healthcare insurance provider, where some projects were about the healthcare side of things, as opposed to the insurance business. The position was shared between a university hospital and the computer science institute. I applied and got shortlisted, to my surprise. After the first interview, I was still in the race, with only one other candidate left. I was asked to prepare a proposal for research on “Data Science in Population Health” and discussed the proposal with a panel. It needed to be interesting for both the hospital as well as for the computer scientists, so that was an interesting combination of people to please. It was a lot of fun to do, actually, and I was proud of what I presented. The committee said they were impressed and the choice was difficult, but the other candidate was chosen. The main reason was supposedly my lack of a recent scientific track record.

What to think of that? The lack of track record is very apparent. It is also, I think, understandable. I have a full time job next to my private/family life, so there is very little time to build a scientific track record. I have gained very relevant experience in industry, which in fact could help academic research groups as well, but you can’t expect people to build experience in a non-academic job and build a scientific track record on the side, in my humble opinion. I was offered to compete for a prestigious postdoc-like fellowship at the hospital for which I could fine-tune my proposal. I respectfully declined, as that was guaranteed to be short-term, after which I would be without a position again. In fact, I was proud to end with the silver medal here, but also slightly frustrated about the main reason for not getting gold. If this is a general pattern, things would look a little hopeless.

As part of my job, and as a freelancer, I have spent a lot of time and effort on educational projects. I developed training material and gave trainings, workshops and masterclasses on a large variety of data science-related topics, to a large variety of audiences. Some of those were soft skill trainings, some were hard skill. Most were of the executive education type, but some were more ‘academic’ as well. When at the astronomical institute at biking distance a job opening with the title “Teaching assistant professor” appeared I was more than interested. It seemed to be aimed at Early Career Scientists, with a very heavy focus on education and education management. Contrary to far most of the job openings I have seen at astronomical institutes, I did not have to write a research statement, nor did they ask for any scientific accomplishment (at least not literally in the ad, perhaps this was assumed to go without saying). They asked for a teaching portfolio, which I could fill with an amount of teaching that must have been at least on par with successful candidates (I would guess the equivalent of 6 ECTS per year, for 3 years on end, and some smaller, but in topic more relevant stuff before that) and with excellent evaluations all across. Whatever was left of the two pages was open for a vision on teaching, which I gladly filled up as well. Another ingredient that would increase my chances was that this role was for Dutch speaking applicants and that knowledge of the Dutch educational system was considered a plus. Score and score. That should have significantly narrowed the pool of competitors. In my letter, I highlighted some of the other relevant experience I gained, that I would gladly bring into the institute’s research groups.

Right about at the promised date (I was plenty impressed!), the email from the selection committee came in! “I am sorry that we have to inform you that your application was not shortlisted.” Without any explanation given, I am left to guess what was the main issue with my application here. I wouldn’t have been overly surprised if I wasn’t offered the job, but I had good hopes of at least a shortlist, giving me the opportunity to explain in person why I was so motivated, and in my view qualified. So, were they in fact looking for a currently practicing astronomer? Was research more important than the job ad made it seem? Is my teaching experience too far from relevant, or actually not (good) enough? Dare I even question whether even this job ad was actually aiming for top-tier researchers rather than for people with just a heart (and perhaps even talent) for teaching? It’s hard to guess what the main reason was, and I shouldn’t try. One thing I am reluctantly concluding from this application is that a job in professional astronomy is hard to get for somebody who has long left the field. I think this vacancy asked for experience and skills that match my profile very well, so not even being shortlisted says a lot to me. Perhaps that’s not grounded, but that’s how it goes with sentiment, I guess. Perhaps a dedicated data science job in astronomy is still feasible, who knows.

In September, I’ll join the University of Amsterdam.

But alas, as said, I have also applied successfully. Yay! The University of Amsterdam (UvA) had an opening for a lead data scientist in the department of policy and strategy. Working for, rather than in higher education was something that previously didn’t really occur to me, but this really sounds like an opportunity to do what I like to do and do well, in the field where my heart is. The UvA is putting emphasis on data literacy in education as well as (inter-disciplinary) research. Big part of the job will be to build and maintain a network inside and outside of the university with data science communities. The Amsterdam Data Science Center fosters research that uses data science methods and meets around the corner. I will strive to take a central, or at least very visible role in that Center and be very close to academic interdisciplinary research! I’m excited! In due time, I’ll report on my experience.

I regret quitting astrophysics

In 2013 I decided to quit my career in astrophysics, move back “home” and become a data scientist. The blog post I wrote about my decision was probably my best read publication as a professional astronomer and it was moving to read all the reactions from people who were struggling with similar decisions. I meant every word in that blog post and I still agree with most of what I said. Now, 7 years after the fact, it is time to confess: I deeply regret quitting.

This post is meant to give my point of view. Many people who left academia are very happy that they did. Here I present some arguments why one might not want to leave, which I hope will be of help for people facing decisions like these.

I miss being motivated. In the first few years after jumping ship many people asked me why I would ever wanted to not be a professional astronomer. I have always said that my day-to-day work wasn’t too different, except that what I did with data was about financial services or some other business I was in, rather than about galaxies and the Universe, but that the “core activities” of work were quite similar. That is kind of true. On an hour by hour basis, often I’m just writing (Python) code to figure things out or build a useful software product. The motivation to do what you do, though, is very very different. The duty cycle and technical depth of projects are short and shallow and the emphasis of projects is much more on getting working products than on understanding. I am doing quite well (in my own humble opinion), but it is hard to get satisfaction out of my current job.

I miss academic research. The seeds of astronomy were planted at very young age (8, if I remember correctly). The fascination for the wonders of the cosmos has changed somewhat in nature while growing up but hasn’t faded. Being at the forefront of figuring things out about the workings of the Universe is amazing, and unparalleled in any business setting. Having the freedom to pick up new techniques that may be useful for your research is something that happened to me only sporadically after the academic years. The freedom to learn and explore are valuable for creative and investigative minds and it doesn’t fit as well in most business settings that I have seen.

I miss working at academic institutions. The vibe of being at a large research institute, surrounded by people who are intrinsically motivated to do what they do was of great value to me. Having visitors over from around the globe with interesting, perhaps related work was a big motivator. That journal clubs, coffee discussions, lunch talks, colloquiums etc. are all “part of the job” is something that even most scientists don’t always seem to fully appreciate. Teaching, at the depth of university level classes, as a part of the job is greatly rewarding (I do teach nowadays!).

I miss passion and being proud of what I do. The internet says I have ”the sexiest job of the 21st century”, but I think my previous job was more enjoyable to brag about at birthday parties. I can do astro as a hobby, but that simply doesn’t give you enough time to do something substantial enough.

I don’t miss … Indeed, the academic career also had its downsides. There is strong competition and people typically experience quite some pressure to achieve. The culture wasn’t always very healthy and diversity and equality are in bad shape in academia. Success criteria of your projects and of you as a person are typically better motivated in business. The obligatory nomadic lifestyle that you are bound to have as an early career scientist were a very enjoyable and educational experience, but it can easily become a burden on your personal life. The drawbacks and benefits of any career path will balance out differently for everybody. If you get to such a point, don’t take the decision lightly.

The people who questioned my decision to become an extronomer were right. I was wrong. It seems too late to get back in. I think I have gained skills and experience that can be very valuable to the astronomical community, but I know that that is simply not what candidates for academic positions are selected on. On top of that, being geographically bound doesn’t help. At least I will try to stay close to the field and who knows what might once cross my path.