What’s next for the blog

Although I have been blogging for a while, it doesn’t happen often that a post gets shared as “Goodbye, tenure track” was. The downside is that any follow-up post will be anticlimactic. While trying to choose a topic to blog about (from several drafted posts) I realized I was procrastinating. So, what’s better than to share these thoughts, and what I’m planning to blog about in the next year.


The most popular topic by far! Recently I’ve been doing events about what I’ve learned about failure so far, and while doing so, several ideas emerged, that I want to write about. I have also started searching for people to interview for season of How I Fail, if you want to join you can leave me a message here.

(Tenure Track) Tips

Perhaps a bit strange from somebody who is leaving the tenure track, but I think I still have a few things to say that might be helpful for any early career researchers.


Following our “Ten Simple Rules for Getting Started on Twitter as a Scientist” paper and the corresponding attention, I have been getting some more follow up questions about how I use Twitter so I’d like to share a few tips for this as well.


If there’s anything else you’d like to hear about, please leave a comment or get in touch on Twitter!

“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.

Not-so-supervised learning of academics

Picking up where I left off with blogging last year – this is part two of a write-up of a talk I’ve given a few times last year, part one is here. After talking about algorithms which deal with data that is not fully labeled, in this part I discuss how career choices can be similar, with my own as an example.


Doing a PhD was not on my radar until my MSc supervisor suggested that I apply for a position in the group. I liked the group and doing research for 4 years seemed like a good job to me (see my post on being an employee during your PhD). I didn’t have any specific long-term goal and, as I now realize, was clueless about most aspects of academia. 

What I did understand is that it was good to publish papers. I had a few interesting (though not spectacular) results fairly early on, so I wrote papers and sent them to various workshops. I enjoyed these workshops a lot – since there were not that many people, I could meet researchers I’d just been citing, and have good discussions. On the other hand, I spent quite a lot of time writing smaller papers and pushing away the fact that I needed journal publications to graduate. Also, as I discovered later, my grant reviewers have never heard of these workshops, and thus were not impressed with my publication record. 

I also did a lot of service and outreach activities. I had already been doing this type of thing as a student, so I was good at it, I enjoyed helping others, and it was good for my CV, whether I’d stay in academia or not. So I spent time organizing workshops, reviewing papers, giving talks to encourage more girls into science. I did learn something from all of these activities but in retrospect I think I spent a disproportional amount of time on them. 


I doubted a lot before deciding to go for a postdoc. The awareness of the struggle of finding a position after, and all the people telling me I really have to go abroad to have any shot at it, didn’t help. In the end by talking to more mentors, I decided to go give it a try – without leaving the country. 

My plan was to only do one postdoc and then get an independent position – or leave academia.  As I understood to achieve an independent position I needed to do three things: publish on the project I was hired on, develop my own line of research, and get my own funding. I was not prepared to deal with so many different objectives, so in the end, I did all the things poorly. On top of that, I failed to take care of myself, and had to take a few months off to recover.

It was during a particular low point during the postdoc that I started blogging and tweeting more. It started with me publishing my CV of Failures – I thought I would be documenting a story that would end with me leaving academia. The response was overwhelmingly positive, and I continued with the How I Fail series. During all of this I found an incredibly supportive Twitter community, with many others who were going through similar struggles, and it’s been helpful ever since. 

Tenure Track

Much to my surprise (and other feelings), I did find myself in a tenure track position after all.  This is an important accomplishment, but at the same time, the next goal – getting tenure – is coming up in a few years. Again, there is this (self-imposed?) pressure to do all the things, so it is not without challenges.  But, it is a much better experience in several aspects, because I occasionally realize that I don’t have to do all the things all the time. :

  • I occasionally realize that I don’t have to do all the things all the time. I’ve now actually been able to have periods on time focusing on writing, then focusing on teaching etc. 
  • I occasionally (not often enough) realize that I don’t have to repeat the career paths on others to “succeed”. The combination of things that I do, might just be “good enough”, even though it doesn’t fit the typical “successful” CV. 
  • I have a lot of people, online and offline, who share or have shared many of the same experiences, and who have advice, or are just up for having a coffee or a beer when things are tough.

Academia as supervised learning 

Where does the not-so-supervised learning come in? It seems to me that a lot of advice of what we need to do to “succeed” is based on rules derived from previous “successful” CVs – publishing at particular venues, doing a postdoc abroad, etc. Some of these rules we are explicitly told as advice, others we assume ourselves.

But there is a lot of missing from this picture. The “success” label is a function of much more than particular activities, but also the state of the world (number of tenure track positions, number of students, etc), and the state you are in yourself (including anything else you have to deal with next to the job search). These features have not been taken into account when creating the rules. So even if you do follow all the rules you might get a disappointing outcome, and vice versa.

There might also be opportunities that didn’t exist before. For example, few full professors would have been using Twitter during their PhDs and postdocs. As a yet “unlabeled” activity, it probably wouldn’t come up in any rules, but it can be a powerful tool for early career researchers.

Last but not least, it’s important to remember there’s more than one success metric, and why I’ve been writing “success” in a CV sense. Ultimately success should probably involve being happy, which can be achieved through other types of jobs. And perhaps some of these jobs are not even in our dataset yet.

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