Performance only becomes relevant with very computationally intensive projects. In research, the bottleneck is rarely computational time, it’s almost always human time. It isn’t, because human time is more valuable than computer time. When I started out I though fast computations would be the deciding factor for or against any programming language. Performance is less important than you thinkīeginners consistently overestimate the importance of performance or speed. It might be worthwhile to defy lab culture and choose a more common language. Either way, keep an eye out for labs that use niche programming languages. A non-academic stack will likely involve at least passing familiarity with more than one programming language.
Pd programming language list software#
A stack is a collection of software (including some programming languages) and people will be hired for “full-stack” or subsets of that stack. You will probably have to learn more than one language anyway. If you learned programming during your PhD you will be in a great position to pick up another language. However, I cannot give a definitive answer and these job markets evolve rapidly. I will go through some programming languages later and give my opinion on their usage inside and outside academia. Otherwise, check your plan B job market for programming languages that are required or advantageous. Then you should fall back to the conformists way. Maybe it doesn’t involve programming at all. I recommend making your plan B as concrete as possible. Other times a lab was simply unable or unwilling to transition to a more common language. Sometimes very specific research requires a niche programming language. While many programming languages are used both inside and outside of academia, some labs use programming languages that are nearly worthless in the non-academic job market. It is considered good practice to have a plan B. Even if you are committed to academia, this point is worth considering. Many of us are not looking to stay in academic research. Which languages are used outside academia In a nutshell, you will be less productive in the short-term but more productive in the long-term, if you choose your programming language well. If you do so, this will affect your work. But there are some other things to consider and sometimes it can pay off to deviate from lab culture. You probably don’t know better than your future colleagues (yet). So why would you want to miss out on those advantages? In short: you don’t. That means your programming experience will help you find a postdoc job if you want to stay in that field. Third, your colleagues are successfully contributing to the field so it is likely that other people in the same field are using the same programming language. You will be able to grab scripts and functions from your colleagues and you will be able to move on from programming details to solving your actual task much faster. Second, you will find many solutions ready to use. First, you maximize the people that can help while you are learning and while you are engaging with the technical details of your tasks. Let me first tell you the many advantages, before I explain why you might benefit from choosing another language. Most people will benefit greatly from this conformist route. I actually brought a language to my lab that nobody else there was using. This conformist approach is not satisfying for everyone. You can do so by reading papers, job advertisements or by directly writing to other PhD students and postdocs. If you don’t know your lab yet but you know the field, try to find out which language dominates that field. If the lab uses multiple languages try to find out what kind of task you will have, find the people with similar tasks and find out which language they are using. If you already know which lab you want to join, find out which language is used there. More important than the technical details are the community, research field and laboratory you want to join. Most programming languages are amazing and the technical differences between them are small and only relevant under special circumstances. Here I’ll guide you through the things to consider when choosing your first or second programming language. At the same time, the programming language you pick will strongly influence your work as a PhD student or postdoc and the opportunities you have afterwards. You can’t go wrong with any of them and they are all worth your time. The good news is that most programming languages that are relevant today are solid. There are many programming languages out there and committing to one of them can be intimidating.
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