A song about academic rejection

So far I’ve only used YouTube to share talks, for example about my research or failure in academia. Today is different, because I’m proud to share with my latest project – Jolene, a song about academic rejection!

I wrote the lyrics back in 2017, and several people on Twitter suggested I should also record myself singing. The idea sounded great but I was also too scared of even trying.

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But 2020 is the year this changed! After Matt Wall shared his MRI song (a cover of “You shook me all night long” by AC/DC), I talked to him about an academic version of Jolene. As things often go on Twitter, turned into a project! Having another person involved made it easier for me to actually get it done, and Matt’s music & production skills made me confident enough to share this with all of you 🙂

Please enjoy Jolene – a song about academic rejection!

Guest post: A CV of Failures in Data Science

As I recently shared on Twitter, my husband Mattias Hansson recently found a senior data science position, after a year long job search process in The Netherlands. He doesn’t really do social media, but you can see his profile on LinkedIn. In this special guest post, I invited him to share something about this process.

[The text from here on is from Mattias’s perspective] 

A bit about me

I grew up in the forests of Sweden in the region of Småland, but I was born in the capital Stockholm. I received a master’s degree in Mathematics from Linköping University, and a Ph.D in Mathematics from Lund University. The title of my Ph.D thesis is ‘Statistical segmentation and registration of ultrasound data’. I did a post doc at the University of Copenhagen at the Department of Computer Science, where I constructed algorithms for defect detection in lumber (a collaboration between university and industry). During my time there I met Veronika, and in 2015 I moved to the Netherlands where I started working at Erasmus Medical Center in Rotterdam as a scientific programmer and researcher. I worked on setting up infrastructure for imaging genetics research, as well as doing research. Additionally I have briefly worked in digital marketing and with my own company. 

Currently my interests are primarily in computer vision, machine learning and statistics. I love to dig into the mathematical details. I am an old rock-climber (20 years experience), but since my shoulder started bothering me I have now transitioned to long-distance walking and running. I love beer festivals and I used to travel every year to Germany (yes, I own a pair of lederhosen), even though this seems like a thing of the past. We also love BBQing, which fortunately we were still able to do during lockdown. 

My job search

I started my job search in November 2019, with the pandemic hitting a few months later. In total I estimate I applied to at least 50 positions, but probably closer to 75 positions, since I didn’t always keep track and never heard back from some applications. Most of these were data scientist positions, unless mentioned otherwise.

  1. Roamler International
  2. FindHotel 
  3. PlotWise 
  4. Amsterdam Data Collective
  5. ABN Amro – Junior Quant
  6. Gemeente Amsterdam 
  7. Quantillion Technologies 
  8. Werkspot
  9. WCC 
  10. Catawiki 
  11. Domino’s Pizza 
  12. Ydigital 
  13. Erasmus MC – postdoc
  14. TU Delft – postdoc
  15. TU Eindhoven – postdoc
  16. Achmea
  17. ASML
  18. Danone
  19. DSM
  20. Elsevier
  21. e-Science Center
  22. Fugru
  23. Numbrs
  24. Quades
  25. SwissRE
  26. Tripaneer
  27. ViQtorDavies
  28. Wikimedia
  29. Aon
  30. CoolBlue
  31. Adyen
  32. Alt
  33. Beat
  34. Bol
  35. CasparAI
  36. Exact
  37. Greeniant
  38. Itility
  39. NCCGroup
  40. RijkZwaan
  41. TU Delft – scientific programmer
  42. Geronimo AI
  43. Lely
  44. PrimeVision
  45. Qualogy
  46. Riviq
  47. Agro
  48. LINKIT
  49. WinBee
  50. Forecast
  51. Mollie
  52. Huawei
  53. MyTomorrows
  54. Priva
  55. Agap2IT
  56. EMEA

There were a number of bad experiences, which I summarize below. 

Problem 1: Level of interviews

Something that happened in several places is that all interviews were conducted by somebody without a mathematics/computer science background. At one company I had 5 interviews, of which 3 on-site. These were led by a consultant which said some incorrect statements about mathematics, and did not appreciate me correcting these. 

At a start-up, I was quizzed using typical “Google interview questions”, and they expected that I would know many of these answers by heart. Of course, the salary was nothing like at Google. A similar thing happened at a large financial company, where I was expected to answer a question about a specific bug in a Python library. 

Problem 2: Profiting from your work

Other companies had a more fitting process, involving some kind of take-home programming assignments. These were interesting, but would take me 2-3 days each. Some of these companies then completely ghosted me, even though I’ve had several interviews. I’m also suspecting that some companies use this to get free quick solutions to their problems (these were not entry-level programming assignments). 

I’ve also only had bad experiences with recruitment consultants, who promise to find you an assignment and call every week, which costs you time, but never gets you anything. It’s a mystery to me how they stay in business. 

Problem 3: Not honoring agreements

Several companies ghosted me after having several interviews, or would only get back to me weeks or months after what was agreed upon. The most memorable example is a multinational company where we had agreed I was interviewing for a mostly-remote job. Once I had finished the interviews and assignment, they announced they wanted me to move to a different country anyway.  

Lessons learned

If I had to do this again, I would avoid recruitment consultants – they are the true definition of a waste of time.

I would probably apply to less jobs, and would step out of the process as soon as there were any bad signs. But I understand that not everyone is able to do this, and might need to take a job as soon as possible.

Maybe the best tip is to avoid the “sunk cost fallacy” – don’t think because you spent a lot of effort on getting a job, that you should stay there – things may still go differently.

***

Thanks for sharing your story Mattias, nice to have you on the blog <3

Guest post: “Avengers for Better Science” has made me a Better Human

Last year together with Aidan Budd, Natalia Bielczyk, Stephan Heunis and Malvika Sharan we organized the Avengers for Better Science workshop. This guest post has been written by one of the participants, Cassandra van Gould-Praag, reflecting on this workshop.

Cass (@cassgvp) is a postdoctoral researcher at the University of Oxford Department of Psychiatry. She provides support for (f)MRI experimental design and analysis in the investigation of treatments for mood disorders. In this role, she has to stay up to speed with the leading edge of analytic tools, and is constantly on the lookout for tips, tricks, and techniques to make this research quicker, slicker, and more effective. This goes hand-in-hand with making the research more transparent and reproducible, and freely sharing the outputs of our labour. She is a contributor to The Turing Way and works with the Wellcome Centre for Integrative Neuroimaging Open Community Team. She is a passionate believer in accessibility and the equitable dissemination of knowledge, and spends a lot of time showing people that programming isn’t scary.

“Avengers for Better Science” has made me a Better Human

Avengers for Better Science” was unlike any academic event I have been to in my 10 year academic career. It will henceforth be my benchmark for collaborative, interdisciplinary, in-person, professional interactions, and a working demonstration of the level of compassion, empathy, understanding and genuine desire to “be better” which is necessary to create the type of research environment I want to be a part of.

I firmly believe that the best tool available to researchers for improving our understanding of the world is to increase the reproducibility of our research. Reproducibility goes hand-in-hand with increasing the diversity of the people who can attempt to reproduce our research; if the only people who can reproduce my work are people who are similar to me, then my work is not reproducible. The added bonus of improving the diversity of contributors is a larger potential reviewing pool. The more eyes which look, the more diverse the viewpoints which can be drawn on to solve problems, and the more likely they are to pick up errors or suggest improvements. This way of thinking underlies the “selfish reasons” to be mindful of inclusivity in research.

I try in my daily life to be aware of issues of inclusivity, but this is not for selfish reasons. This is because life is hard, and for some people life is extra hard, and I’m not about adding to the discomfort. You might call me a “Social Justice Warrior”, and I’d be fine with that. Our society deserves justice and I’m prepared to go into battle. 

The skillfully crafted program of talks and events at Avengers allowed me to demonstrate the value of understanding my own privilege as a white cisgender heterosexual non-disabled person. It also compounded the understanding that my own experience of the world may be very different to someone else’s. This position is supported by my empirical research on perception and conscious experience (for example exploring the experience of synaesthsia) which supports the idea that there is no reality except that which we perceive, and everyone’s perception is personal. 

Despite my pre-existing understanding, I had ample opportunity to learn at Avengers. I was challenged on my assumptions, reminded of the ethical imperative to be kind to myself if I want to do my best work, taught how to support others (and myself) at times of crisis, given some excellent productivity tips, and convinced for the first that there is a research environment which exists outside of academia that I could thrive in. I was also made aware of some ethical concerns in how we practice research, for example in the use of biased artificial intelligence to inform criminal sentencing, and ideas of situatedness when we consider who is leading the agenda on transparent and reproducible research. 

All of these lessons wildly exceed anything I learnt in institutional “Professional Development” courses. This was in no small part due to the excellent leadership demonstrated by the organisers as they all enacted the core values of community and inclusivity which they were aiming to foster within attendees. They worked tirelessly to build a safe space to explore our strengths and weaknesses, and made it abundantly clear that it was “OK” to be vulnerable and less than perfect. This is a lesson which is sorely missing in academia. They helped us to remember that we are all human, and that is an excellent thing. 

The funded travel and accommodation for the workshop meant I didn’t have to work too hard to justify attendance to my department. If I had, I may have struggled to define how “learning to be a better human” would help me do better research. I now understand that acknowledging my humanity makes it easier to accept my mistakes and those of others. This makes me far more open to constructive criticism, which in turn makes it a lot easier to ask questions and comfortably share my code and data. It also helps me to hold my beliefs lightly, which may reduce the bias I bring to analysis. 

An improved understanding around issues of inclusivity allows me to interact more effectively with our volunteer participants, design more ethical research and have a greater awareness of the ethical impact of our work and that of others. It also makes me a better colleague and teacher. I work harder to listen to my colleagues and students, and place more value in their truth. This makes the process of collaborative research (which all research is) much more efficient, effective and enjoyable. I’m also trying to to lead the culture change which is necessary for a healthy academia by taking care of myself, managing my own expectations and that of others, while openly and directly challenging behaviours which violate the rights of others. I am more productive now I understand my own limiting beliefs and am able to communicate my requirements with confidence.

Success in academic research is in part governed by “who you know”. I am therefore sincerely thankful to the organisers and attendees of Avengers for the community that we built at the event and networks which we continue to strengthen. Through open and inclusive research projects I know that it is possible to work as part of a team with shared values, and this usually makes for a pretty fun and productive project. I know that the connections I made through attending Avengers will stay with me throughout my career, and I am excited about the opportunities for collaboration this brings. This passion and curiosity is an excellent motivator for me. I look forward to the next opportunity to learn from my kind and diverse colleagues.

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