How can I make my code faster? How can I make my code more reliable and reproducible? How to scale up to larger datasets? Is this the best way of approaching this problem? Is there a library for this? How can I test this? Can I do this on a cluster instead of my laptop? How can I package my library?
There are many questions that come up when developing research software, and researchers are always welcome to get in touch for a consultation. In addition, many of our consultations develop into small scale development projects that are free of charge and involve about a week of development work by our Research Software Engineers.
A consultation about parallelization in Python from a researcher analyzing mutations in SARS-CoV-2 led to a small scale project where we implemented a highly optimized, vectorized and parallelized C++ version of the performance critical part of their pipeline, allowing them to process vastly larger datasets.
We helped a researcher to package their C++ library using CMake within a single one hour consultation, significantly improving the portability and usability of their software.
The AMMICO project from our 2022 Open Call started life as a consultation about analyzing misinformation in social media, which then evolved into a successful small scale project before later becoming an Open Call project.
Coming from theoretical physics, I kind of know how to code, but when it comes to writing software I quickly notice some large gaps. It was a delight to work with the SSC on these questions, reactions were always quick and competent. In the end, our software was more professional and easy to use, and saved my team and me a lot of time.
Ricardo Weibel, PhD student