We want to make our candidate selection process as open as possible. Generally we’re not trying to hire people who can solve software problems on the acute timescale and in the pressured situation of a job interview, so maybe it’s best to share some example interview questions and assessment tools with everyone?

This is a representative example, and gives an idea of what to expect, but the process we use for any specific role may differ somewhat.

We have a job advert out for an RSE! Here are six reasons to apply:

1. Varied projects. We work on research in areas such as astrophysics, healthcare, molecular biology, civil engineering and many more. Maybe you’ve been working on one area for years and you’re keen to work with researchers in diverse fields?
2. We don’t need an expert in everything right away. Lots of people have joined our team having developed coding skills working on research, and learned more software engineering once in the team. Our team is made up of people who specialise in sharing software engineering skills with researchers.
3. Make a difference. Our team works with public/private sector organisations, and charities to give our output the best chance of making a positive difference outside the university. We also enthuse about and participate in open research wherever possible.
4. Flexibility. We’re happy to discuss flexible and part time working options. One of our team has recently reduced their hours from 100% to 80%. Working as a pool makes this much more practicable. Furthermore, in contrast to most RA roles this position is open-ended.
5. Do useful stuff with code. We are most interested in your ability to do useful things with code and work with other people. We don’t tend to ask questions about the theory of computer science in interviews. The interest is in modern software technology, code you’ve written, how it was used and how it could be improved.
6. Reward and recognition. All of the Sheffield RSE team are employed within the academic careers pathway, a new flexible career development structure which recognises a broad range of research outputs including software. The pathway provides a clear route for promotion up to the level of professor.

Please view the advert to apply, and see contact details for enquiries about the job. General enquires about the team are welcome at rse@sheffield.ac.uk.

In research, it is of utmost importance to the scientific process to be able to reproduce research findings in order to establish their validity. However, more often than not, the code that is written for research purposes cannot be easily run again, sometimes even by the code’s authour (yours truly included!).

This year, I’ve been awarded a fellowship by the Software Sustainability Institute to develop guidance and training to help researchers who use MATLAB to find and learn the tools that they need to easily produce better research by making their code reproducible.

During my PhD and postdoctoral research, I used MATLAB, among other languages, to analyse data, run simulations, make figures and control instrumentation. However, at the time, I didn’t know about the concepts required to make my code reproducible for myself and others. Over the last few years, as a Research Software Engineer, I’ve gained the experience needed to develop reproducible software in a range of languages including MATLAB. Now it’s time to share what I’ve learned with everyone!

This blog post should serve as a very brief set of signposts to some of the concepts you can use to develop a reproducible project in MATLAB. You can expect more to come throughout my fellowship, so watch this space.

If you’ve been dabbling in programming for a while you may have heard of “linting your code” which is a process of static code analysis to remove the “fluff” from your code. Just as physically linting your clothes removes unwanted fluff, linting your code removes “fluff” and can help…

• Reduce bugs.
• Improve performance.
• Mitigate against some security flaws.
• Improve coding skills.
• Consistent coding style.

This helps reduce the technical debt which impacts the amount of time required for maintenance and further development of a code base. The main focus of this article is the use of linting to ensure consistent coding style, it focuses on Python under Linux but similar tools are available for other operating systems and languages.

Due to team member relocating to another country (😥) we have an RSE role in the team at the University of Sheffield. It is role where we are specifically looking to recruit someone with skills in R.

Are you interested in joining a team to develop and facilitate reproducible software through collaborations across the whole spectrum of university research areas?

Bob Turner from the RSE Team gave a talk at SeptembRSE! Video is now available…

Software is an important part of research and a key research output. We conducted a survey at the University of Sheffield in October 2020, similar to previous surveys conducted nationally and at the University of Southampton, to find out about how software was being used in research.

Are you interested in leading a team to develop and facilitate reproducible software through collaborations across the whole spectrum of university research areas?

A brief intro to where Machine Learning fits into the work of the University of Sheffield RSE team.

See some examples of Machine Learning projects and training Introduction to Deep Learning, Fundamentals of Deep Learning for Computer Vision Workshop.

The team was recently asked to speak to a first year undergraduate Computer Science course with a view to introducing students to concepts in research software engineering, including some which they might use in their upcoming projects. The talk recording is embedded below, it starts at the beginning of the video and ends at roughly 55 mins. Alternatively, watch on The University of Sheffield digital media platform.