Students are starting to fill the campuses, leaves are turning yellow and brown, days are becoming shorter and, while weather is still good - indeed somewhat nicer than during the really hot past summer - it is clear we are entering a new season. I really like Autumn. Keeping aside the beautiful colours of parks and forests around London, it feels like a good time to start new things in a sustainable manner (not like pointless New Year resolutions…). It might be stressful at times, but also an opportunity to try new things to make it work.
Research software and our community are no different. Last month, we launched Imperial’s Research Software Directory - you have submitted your software already, right? - and soon, we will have available Imperial’s brand new HX3 cluster for AI computing. New courses and training are popping up to help researchers perform their computational work more effectively, including those organised by the Research Computing and Data Science team. And, as always, we are never short of conferences to mingle with the wider community. So take a break from your daily routine, grab a coffee and have a look at all the interesting offers that we are bringing you in this newsletter.
Are you worried about the environmental impact of your use of high performance computing? Then the course on Green software use on HPC, on the 2nd October in Cambridge (in person only), is for you. Register before it is too late!
Applications are now open for the Institute for Research Software Fellowship Programme 2027 (submission deadline: Monday 5th October 2026). The Fellowship Programme funds researchers, research software engineers, and advocates who want to improve computational practice in their field. The programme is open to applicants at any career stage and from any background, from PhD candidates and junior research software engineers to professors and directors of research computing, including those without a formal software background who support research, training, or research infrastructure.
The Research Data Alliance Plenary is coming to London! The RDA’s 27th Plenary Meeting (P27) will take place in person at the Kia Oval in London, from the 6th-8th October 2026, hosted by UKRI. Standard event registration is open.
Do you have concerns about the reproducibility of your research? Then you might be interested in learning about containers, and how they can support reproducible computational workflows. Join the course on Containers for Reproducible Research: Introduction to Podman and Apptainer, at Imperial (in person only) on Wednesday 7th October 2026. Registration is mandatory.
The next Research Software Camp (RSC) will be delivered as a multi-session event over the course of two weeks from 26th October to 6th November. Sessions will use the Byte-sized short-format training model, developed by Imperial and the Institute for Research Software in the UNIVERSE-HPC project, to offer training in a set of key RSE-related topics. Attendees are welcome to attend any of the sessions that are of interest to them, free-of-charge. Registration opens on Wednesday 30th September - see the event page for registration details.
The next Research Infrastructure Engineer (RIE) Community and Co-design Days will be in in Edinburgh (11th November) and Bristol (24th November)! These events are a chance for the RIE community to come together, share knowledge, and help shape the future of HPC infrastructure training. Registration is mandatory and on a first come, first serve basis! If you are an RIE interested in delivering a talk, and not just attending, send email to ACIT@surrey.ac.uk with a brief outline of your talk. They can cover travel and accommodation costs for speakers. For more information on upcoming RIE Community and Co-design Days, please see the University of Surrey’s ACIT Hub events page.
Applications are now open for the DisCouRSE project’s funding round 3, supporting the development of leaders across all digital Research Technical Professional (dRTP) roles. Submissions close at 16:00 GMT on the 11th December 2026 for this latest funding call, which allows longer and larger projects than before. This third call has two strands:
In this month’s Research Computing at Imperial feature, we’re featuring another group of our STEP-UP Digital Research Technical Champions. In this edition we hear from Callum Tilbury, Raj Bhavsar and Aaron Mamane-Logsdon… who each tell us a little about their research and their motivation for joining the Research Technical Champions programme:
I am a second-year Bioengineering PhD student working in the Non-invasive Surgery and Biopsy lab, supervised by Dr James Choi. Our lab works on transcranial focused ultrasound for targeted drug delivery, using micron-sized bubbles to safely and reversibly open the blood-brain barrier. Such an effort requires a wide range of disciplines, and we have diverse backgrounds: chemistry, pharmacology, physics, biology, electrical engineering, microfluidics, and more! My work covers the computational aspects of the problem, which means it sits alongside many of these domains—utilising modern computing tools to improve our science. To this end, I am also co-supervised by Dr Ben Moseley in the Scalable Scientific Machine Learning lab. Thus far, my work has primarily looked at using differentiable physics in the context of microbubble dynamics for gradient-based parameter inference, but I also work on large-scale acoustic simulations, generative modelling for inverse problems, and general science automation with hardware-in-the-loop.
Before starting my PhD, I was an AI research engineer in industry for ~3 years, and I spent much of that time thinking about good research infrastructure—how can supporting tooling maximise the effectiveness and reliability of our science output? That is the angle I try to offer my group and our multi-faceted discipline. Furthermore, this is what encouraged me to become a STEP-UP Champion: I have been engaging first-hand with the joys and challenges of next-generation methods in the context of hard science, and I truly believe there has never been a better time to accelerate our workflows. But the waters remain precarious and unclear for many—that is the bridge I am working on building.
I’m a PhD researcher in Chemical Engineering at Imperial, working at the intersection of process systems engineering, energy systems modelling and machine learning. My current research focuses on developing spatiotemporal graph autoencoders to model complex energy systems, which involves working with large datasets, computational models and research software workflows.
I became a STEP-UP Champion because I’ve seen how strongly good digital research practices can influence both the efficiency and quality of research. Researchers increasingly rely on code, data and computing infrastructure, including in disciplines that have not traditionally been computational. However, challenges around reproducibility, version control, project organisation, data provenance and accessing computing resources can create unnecessary barriers. Often, the issue is not a lack of technical ability, but simply limited exposure to the right tools and practices.
Through STEP-UP, I’d like to help make these practices more accessible and practical for researchers. I’m particularly interested in reproducible computational workflows, Git and version control, effective management of modelling and data pipelines, and the use of machine learning in research. I’d also like to explore informal workshops, practical resources and peer-led sessions where researchers can bring real problems and learn from one another.
For me, the Champion role is an opportunity to share what I’ve learned, learn from researchers across Imperial, and help strengthen a collaborative digital research culture.
I am a final-year President’s PhD scholar and computational biologist at Imperial College London in the Department of Infectious Disease. My research focuses on identifying and inhibiting the molecular mechanisms by which human T-cell lymphotropic virus type 1 (HTLV-1) integrates into DNA. To do this, I use Python, statistics, AI/ML, Linux, high-performance computing, data/software engineering, computational omics, genetic variant interpretation, biomolecular modelling, and drug design. In addition to research, I deliver teaching materials for programming and data/software engineering within the college. Through my PhD and teaching, I have noticed that while many in the department have embraced programming as part of their research, few take the step to develop organised, higher-fidelity, version-controlled software projects. Additionally, few fully exploit the state-of-the-art computational support provided by the college’s Research Computing Service, Early Career Research Institute, the library, and more. In my role as STEP-UP champion for the department, I aim to encourage more colleagues to make a habit of using the college’s computational resources and, in the process, foster a confident environment for software engineering.
This month, we hear from Puzzlepiece, developed in the Department of Physics to make their interfacing with hardware a bit easier.
Puzzlepiece is a GUI-forward Python framework for automating experimental setups. It focuses on abstracting communication with a piece of hardware into standard inputs, outputs, and actions. It then automatically generates GUI components for them, minimising the need for boilerplate code. This approach treats the graphical interface as a first-class citizen, allowing live inspection and alignment, while still exposing familiar abstractions on the Python side through a unified API, accessible either by making custom GUI Pieces, with Interactive Python in Notebooks, or through a built-in script language.
In the Complex Nanophotonics group we use puzzlepiece to control a diverse set of experiments, bringing cameras, moving mirrors and stages, spectrometers, and spatial light modulators into unified, modular apps. Depending on the needs of specific group members, they can run their experiments fully in GUI mode, or with a companion Jupyter Notebook used for live, code-defined measurements. This approach has replaced the previous collection of Matlab, LabVIEW, and Python applications, easing the onboarding of new group members and the creation of new experiment GUIs.
Check out the Puzzlepiece documentation for examples and a tutorial, and the existing library of hardware integrations.
The Software Sustainability Institute is no more! At the beginning of September, the institute revealed its new name and branding, Institute for Research Software. This change is to recognise the growth of the research software field and the evolving role of the institute over the last 15 years. Read more in the announcement: Introducing the Institute for Research Software
The first round of the Open-Source Enhancement Fund (OSEF), an initiative of Imperial’s central RSE Team, is now over! The fortunate recipients on this occasion are:
Deploying your own private LLM sounds like a complex, but really cool thing to do, right? With the upcoming launch of Imperial College London’s new HX3 cluster for AI computing, our colleague from the RSE Team, James Turner, has written a post about how to do precisely that, using the Nvidia Run:ai framework. Read the tutorial and unleash your private model to help with your research.
And one more post on AI, in this case, from the RSQKit on AI Guidance and Practice, about the different levels an AI can be used in software development and what measures should be put in place in each case to make an appropriate use of it. Definitely worth a read!
Because inclusivity is what we make of it, this guide on Fostering Inclusive Contribution Models in Open Projects will help you make the right decisions when defining the contributing guidelines of your project. Keep in mind that not having any guidelines at all is a guideline as well about how to do things, so make a conscious decision rather than the default, easy choice.
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.
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:
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.
All the documentation, tutorials and how-tos for using Imperial’s HPC are available in the Imperial RCS User Guide.
Imperial’s Research Software Directory provides details of a range of research software and tools developed by groups and individuals at Imperial. Please, submit your software and help increase its visibility and impact. If you have any questions, get in touch with the Imperial’s Research Software directory maintainers.
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 Diego Alonso Alvarez. All previous newsletters are available in our online archive.