Imperial College Research Software Community Newsletter - July 2026

It’s almost August! Summer is very much here (and going by the weather, it’s been here for a while!). If you’re taking a break over the coming weeks we wish you all a relaxing and enjoyable holiday. However, there’s still lots happening in the research software and digital Research Technical Professionals communities over the coming month. So, if you’re working through August, or you are around for some of the time, do look out for interesting opportunities to join talks or events, or just take a chance to read through some of the resources we’re sharing with you in this month’s edition of the newsletter. The last month has been a busy one for many in the research software community with lots of events and activities. Highlights include our STEP-UP RSLondon 2026 conference which took place at the end of June at the Francis Crick Institute (slides from many of the talks at that event are now online), the Teaching and Training Special Interest Group community days held in Manchester in mid-July, and last week, our green and sustainable research computing workshop held at Imperial’s 170 Queen’s Gate - again, slides are being made available via the event schedule page.

Enjoy the content we have for you this month and, as always, feel free to reach out to the Imperial Research Software Community committee at rse-committee@imperial.ac.uk if you have any questions or ideas for community activities.

Dates for your diary

Research Computing at Imperial

In this month’s Research Computing at Imperial feature, we’re featuring another two of our STEP-UP Digital Research Technical Champions. In this edition we hear from Brianna Austin and David Tsang who each tell us a little about their research and their motivation for joining the Research Technical Champions programme:

Brianna Austin

I am a PhD student in the Department of Brain Sciences at Imperial College London. My research focuses on traumatic brain injury (TBI) and investigates how integrating mechanical information from injury events, such as road traffic collisions alongside advanced neuroimaging can improve prediction of patient outcomes. TBI is a highly heterogeneous condition, with people who present with similar clinical severity often experiencing different patterns of brain injury and recovery trajectories. As a result, accurately predicting outcomes remains a major challenge. My research is built on the premise that because TBI is fundamentally a mechanically induced injury, including information about the forces that caused the injury should improve our understanding of the resulting brain damage and ultimately lead to more personalised and accurate prognostic models.

My research aims to address these challenges by developing computational approaches that combine biomechanics, medical imaging, and machine learning to better characterise injury mechanisms and predict recovery. In doing so, I hope to contribute tools that not only advance scientific understanding of TBI but also have the potential to support future clinical decision making.

Before starting my PhD, I completed the Translational Neuroscience MSc here at Imperial. My MSc project sought to understand whether there was disrupted hierarchical control amongst functional networks in opioid use disorder. Throughout this project, I developed my computational neuroscience skills, gained exposure to machine learning, and different data structures. I experienced first hand both the opportunities and the challenges of learning research software, from navigating unfamiliar programming languages to building reproducible analysis pipelines. These experiences reinforced to me the importance of accessible computational training and supportive research communities.

I applied to become a Research Technical Champion because I want to help make computational research more approachable for others. Many researchers, particularly those from predominantly experimental or clinical backgrounds, can feel intimidated when first encountering programming and research software. As a Champion, I hope to contribute to a culture where researchers feel supported in developing these skills by sharing knowledge, encouraging good research software practices as this will then help to create streamlined and reproducible workflows. My goal is to use my time to lower the barriers to computational research so more researchers can confidently adopt the tools available to them.

David Tsang

I am a PhD student in the department of Chemistry, working at the intersection of synthetic biology, lab automation, and machine learning. I chose to become a STEP-UP champion because I am a strong proponent for good computational practices in fields that are gradually dependant on more powerful computational resources. My research project heavily involves robotics and machine learning, so I am keen to establish good data management, software production, and computing infrastructure practices within my project and promote them to groups adjacent to my research interests. The Chemistry department produces a huge amount of experimental data, meaning that good data management is crucial to maintain accessible and organised databases to build important scientific insights. Lab groups are now developing high-throughput methods to increase research output. When leveraging tools like machine learning algorithms and robotics to build new pipelines, it is important to have robust software development practices. Through this role, I am eager to further develop my own digital research skills and develop my communication skills to share knowledge with other professionals. By standardising these practices, it will allow the democratisation of computing practices to professionals who are not computing experts in an age where intelligent computational tools are spearheading research capabilities.

RSE Bytes

News

Blog posts, tools & more

Some reminders…

RS Community Slack

The Imperial Research Software Community Slack workspace is a place for general community discussion as well as featuring channels for individuals interested in particular tools or topics. If you’re an OpenFOAM user, why not join the #OpenFOAM channel where regular code review sessions are announced (amongst other CFD-related discussions…). Users of the Nextflow workflow tool can find other Imperial Nextflow users in #nextflow. You can find other R developers in #r-users and there is the #DeepLearners channel for AI/ML-related questions and discussion. Take a look at the other available channels by clicking the “+” next to “Channels” in the Slack app and selecting “Browse channels”.

If you want to start your own group around a tool, programming language or topic not currently represented, feel free to create a new channel and advertise it in #general.

Research Software Engineering support

If you need support with your code, seek no more! The Central RSE Team, within the Research Computing Service is here to help. Have a look at the variety of ways the team can work with you:

Research Computing and Data Science workshops

The Research Computing and Data Science team at Imperial’s Early Career Researcher Institute run workshops in programming, statistics, data science, software engineering, Linux, HPC, AI for programming, LaTeX, and much more, which are available to the Imperial community. Follow the registration information on the RCDS page to sign up.

HPC documentation and tips

All the documentation, tutorials and how-tos for using Imperial’s HPC are available in the Imperial RCS User Guide.

Research Software Directory

Imperial’s Research Software Directory provides details of a range of research software and tools developed by groups and individuals at the College. If you’d like to see your software included in the directory, you can open a pull request in the GitHub repository or get in touch with the Research Software Community Committee.

Get in Touch, Get Involved!

Drop us a line with anything you’d like included in the newsletter, ideas about how it could be improved, or even offer to guest-edit a future edition! rse-committee@imperial.ac.uk.

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This issue of the Research Software Community Newsletter was edited by Jeremy Cohen. All previous newsletters are available in our online archive.