Open Science (OS) is a movement that aims to bring about a change to the academic publishing system. Yet, despite being around for over 30 years, it has had relatively limited success. Traditional publishers still dominate the landscape, article processing charges have made publishing less equitable and the whole system is straining under the pressure of increased numbers of papers and a reduced reviewer pool.

When I first started my PhD in France, I couldn’t help but address my PI with the formal “you” in french (“ vous ”), instead of the informal “you” (“ tu ”). She was very quick to tell me to use the informal form. It took some getting used to, but I stuck to it.

We’ve all peeked at that “Received, Revised, Accepted” section of a paper and instantly regretted it. Those dates often read less like a timeline and more like an archaeological record. And that, kids, is why one should NEVER ask a PhD student about the timings of their PhD. From all variables that define the fate of a PhD, one of the harder ones to control is indeed… the peer reviewing process (wow, on a blog that writes about peer reviewing.

… gotcha! You clicked because the title sounded extraordinary, revolutionary, amazing — didn’t it? And for a while, I found myself reacting the same way you just did. Then, spending a good hour reading an article, only to realize there was no real solution inside. Just less bold conclusions, weak predictions even. Some articles are like that — they promise a lot in the title but deliver very little.

“So, what experiment should we do next?” asks the student.  And two different tabs open up side to side in your mind. Tab 1: Taking a stroll in your field In this tab, there are no real rules. You are wandering on the signaling pathways, thinking back to the intersections that you encountered before and at the same time, looking for new ones that could appear in the continuation of this little walk.

The current system of recognition in academia is built on a single pillar; publishing. Career advancement is dependent on how much and where you publish. Assessment of “quality” is based on extremely poor proxies, such as impact factor or journal name. There are a range of costs to this system ranging from financial to personal. Financial The financial costs of publishing are very well documented.

The rise of Large Language Models in academic writing. Postdoctoral researcher Dr Verena Haage was reviewing a manuscript for a reputable neuroscience journal when she began to notice unusual inconsistencies. Haage noticed that some figures had strange proportions, or illogical experimental timepoints, and that figures were arranged in a senseless order.

By the end of my PhD, I was somewhat disillusioned by the way scientific research worked and decided to pick a field that could open up a (small) door to industry, if I ever decided to take that route one day. (I was very naive about that, but that is a story for another time.) After some digging, I could find two labs focusing on the relatively narrow question I wanted to pursue for my postdoc.

Meet Larry, the Scientific Cat Larry — a fluffy, slightly overweight cat — has achieved what many postdocs or even professors only dream of: becoming the most cited “author” in his field. Obviously, Larry has never written a word or attended a conference. His main activities? Napping, demanding food, and scratching furnitures. Yet, there he is — the most cited author without lifting a paw.How Did We Get Here?

If doing your job requires constant applications to keep doing it, is that really a “job”?  Why do we need to keep “auditioning” for work we’re already performing? Let’s first agree that there isn’t a typical career trajectory in academia. But there are some recurring steps one usually has to go through. Getting the job There are definitely some unwritten laws about getting jobs in academia.

We all know this person. Or we are this person. You troubleshoot broken connections in the lab, fix the department printer, teach undergrads how to use the Nanodrop and pH-meter, and share all your best Excel hacks. Congratulations: you're the Swiss Army knife of your lab. But guess what?