What is Research Software Engineering?

In today’s research landscape, computational methods are more important than ever. From data analysis and machine learning to complex simulations and workflow automation, software plays a crucial role in advancing knowledge across disciplines. But who ensures that research software is efficient, reliable, and sustainable? That’s where Research Software Engineers (RSEs) come in. A growing number of people in academia combine expertise in programming with a deep understanding of research. These individuals, known as Research Software Engineers (RSEs), play a crucial role in ensuring that computational tools and software development are integrated into research workflows effectively. Despite their essential contributions, RSEs have historically lacked formal recognition in academia. Regardless of job title, RSEs tend to:

Spend more time developing software than conducting research.
Act as the go-to person for computational aspects within a research group.
Work on software development while being employed under roles such as postdoctoral researchers or technical staff.
Contribute significantly to research outcomes but may not always receive authorship on publications.
Face challenges in career progression due to a lack of conventional academic metrics such as papers and conference presentations.

If you're interested in learning more about the broader Research Software Engineering landscape in the UK, consider exploring the Society of Research Software Engineering. The society advocates for RSEs, supports career development, and connects professionals across institutions. Find out more here: https://society-rse.org/about/.

RSE at Leeds

At the University of Leeds, our Research Computing team provides a centralised service for Research Software Engineering expertise, supporting the entire university. Through our consulting service, we formally collaborate on research projects, offering hands-on software development and technical guidance. Our supporting services provide advice at different levels, from initial project scoping to troubleshooting computational challenges. Additionally, through our teaching efforts, we equip academics with the foundational knowledge needed to integrate computational methods into their research, following best practices from day one. We are also actively engaged in the wider research community, aiming to make research software engineering accessible and impactful for as many people as possible. Whether you're an early-career researcher, an established academic, a postgraduate student, or someone looking to apply computational methods in your field, we help you leverage computational tools effectively, ensuring that your research is robust, reproducible, and impactful.

At Leeds, our Research Computing team offers a wide range of support, including:

Custom software development: We build and refine software solutions tailored to research needs.
High-performance computing (HPC) expertise: We optimise workflows for large-scale computations.
Data visualisation and interactive tools: We create dashboards and visual analytics to communicate research findings.
Workflow automation: We improve research efficiency by automating repetitive tasks.
Software sustainability: We ensure research code remains functional and maintainable over time.

If you’d like to learn more about the areas we can support, explore our consulting catalogue at https://arc.leeds.ac.uk/consulting/. It provides an overview of the expertise we offer and how we can help you apply computational methods effectively in your work.

Got a Research Problem? We Can Help!

Not sure if our team can support your research? Here are some examples of common challenges researchers face, and how we can help:

I have a code that analyses a small sample of my dataset, but when I try to process the entire dataset, it crashes. Can you make my solution scalable?
I need to create 500 plots—I've done two manually, but it's taking too long. Can you automate this for me?
I run the same analysis every few weeks with updated data. Is there a way to make this process repeatable and less time-consuming?
I have a spreadsheet where I manually copy and paste data between sheets for analysis. Can you help me streamline this process?
I want to share my research findings in an interactive way, rather than just using static charts in a PDF. Can you help me build a web-based tool for this?
My code works on my laptop, but when I send it to my collaborator, it doesn’t run on their system. Can you help me make it more portable and reliable?
I have a large dataset stored across multiple files, and I need to merge and clean them before I can start my analysis. Is there a better way to do this?
I need to run a complex model that takes hours to complete on my computer. Can you help me make it faster or run on a more powerful system?
I’ve received feedback that my research should be more reproducible, but I don’t know where to start. Can you help me apply best practices?
I’m writing a grant proposal and need to describe the computational methods I will use. Can you help me make sure I include the right details?
I have survey data that I need to visualise in an engaging way for policymakers and the public. Can you help me create interactive dashboards?
I have raw experimental data that I need to transform into clear and informative graphics for my research paper. Can you help me create effective visualisations?
I need to teach my students basic programming and data analysis skills but don’t know where to start. Can you help me develop teaching materials?
I’d like to integrate hands-on coding exercises into my course, but I’m unsure how to set up a learning environment that works for everyone. Can you advise on best practices?
I’m organising a workshop on computational research methods but need technical support and guidance. Can you help facilitate it?

Yes, we can help! Our Research Computing team supports researchers across disciplines, whether you need advice, automation, or a scalable solution. If any of these challenges sound familiar, get in touch and let’s discuss how we can support your research!

You can also explore real examples of our contributions by visiting our Research Computing Case Studies pages.