Round 2 awards (alphabetically)
The successful projects support more than 25 software packages, platforms, and components. All maintain openly licensed software. Python is used by 11 projects, C++ by six and Fortran by four, with R, C, JavaScript, PHP, Ruby and other specialist technologies also represented. The earliest software was first released in 2004, while the most recent was released in 2025; 12 projects support software first released in or before 2014.
The projects will address challenges including technical debt, testing, documentation, software architecture, accessibility, interoperability, community development, and long-term governance. Four are led by Research Software Engineers or other research technical professionals, and the funded teams involve 25 lead and co-lead organisations.
Team: Stephane Hess, Project Lead, and Georges Sfeir, Project Co-Lead (University of Leeds).
Description: Apollo is an open-source platform for analysing and forecasting human decision-making using choice models. The project will develop a Python interface around Apollo’s established R framework, supported by cross-language testing, documentation and governance, enabling researchers to combine behavioural modelling with modern data-science, AI and machine-learning workflows.
Links: Apollo website | Apollo on CRAN
Domain: Choice modelling, behavioural science and transport research.
Team: Phil Reed, Project Lead; Carole Goble, Project Co-Lead; Finn Bacall, Research Software Engineer; and Munazah Andrabi, Research and Innovation Associate (University of Manchester). Maria Doyle, International Project Co-Lead (University of Limerick).
Description: TeSS is an established registry that helps researchers, trainers and students discover life-science training. The project will automate the collection of Bioconductor training resources using Bioschemas and JSON-LD, reducing manual curation and providing a reusable approach for making research training easier to find, access and reuse.
Links: TeSS | TeSS repository
Areas: Life sciences and bioinformatics.
Team: Nathan Luke Abraham, Project Lead, and Robert Waters, Research Software Engineer (University of Cambridge).
Description: The UK Chemistry and Aerosols model supports climate, atmospheric chemistry and air-quality research, but currently requires specialist Met Office infrastructure. DUBIOUS will deliver a lightweight version that can run on a standard computer and introduce automated testing to improve reliability and make scientific developments easier to transfer into the UK’s operational modelling systems.
Links: UKCA website | UKCA repository
Domain: Atmospheric chemistry, climate science and air-quality research.
Team: Dawn Knight, Project Lead, and Fernando Alva-Manchego, Project Co-Lead (Cardiff University). Two Research and Innovation Associates will be appointed at Cardiff University.
Description: FreeTxt is a secure, open-source toolkit that enables non-specialists to analyse and visualise qualitative text in English and Welsh. Working with public, cultural and educational organisations, the project will improve its usability, reliability and Welsh-language capabilities, establishing it as a sustainable platform for bilingual feedback and survey analysis.
Links: FreeTxt | FreeTxt repository
Domain: Qualitative text analysis, language technology, applied linguistics, and bilingual research.
Team: Phil King, Project Lead, and Shu Mo, Research Software Engineer (University of St Andrews). Robert Palgrave, Project Co-Lead (University College London).
Description: peaks is an open-source Python package for analysing the large, multidimensional datasets produced through photoemission spectroscopy. The project will introduce a plugin-based architecture for facility-specific data loaders, improve testing and remote workflows, and develop training and governance to transition the package towards community-led maintenance.
Links: peaks documentation | peaks repository
Domain: Materials physics and photoemission spectroscopy.
Team: Paul Richmond, Project Lead; Robert Chisholm and Peter Heywood, Project Co-Leads (University of Sheffield). Two part-time Research Software Engineer positions will be appointed at the University of Sheffield.
Description: FLAME GPU enables researchers to run large-scale agent-based simulations on graphics processing units without needing specialist GPU-programming expertise. The project will expand hardware support, including support for AMD GPUs, improve interoperability with Python tools, and strengthen documentation, training, contribution pathways and governance.
Links: FLAME GPU website | FLAME GPU repositories
Domain: Agent-based modelling and large-scale simulation across multiple research disciplines.
Team: David Wyld, Project Lead, and Martin Rogers, Project Co-Lead (British Antarctic Survey). Alejandro Coca-Castro and Louisa van Zeeland, Project Co-Leads, and a Research Software Engineer to be appointed (The Alan Turing Institute).
Description: DeepSensor is an open-source Python package that makes it easier to apply neural-process machine-learning methods to complex environmental data. The project will transition DeepSensor towards a community-maintained model, establish stronger governance and contribution pathways, and grow a diverse community of users, developers and maintainers.
Links: DeepSensor documentation | DeepSensor repository
Domain: Environmental science, geospatial data analysis and machine learning.
Team: Abouzied Mohamed Abouzied Nasar, Project Lead (University of Manchester); Mladen Ivkovic, Project Co-Lead (Durham University); and Matthieu Schaller, International Project Co-Lead (Leiden University).
Description: SWIFT is a UK-led, massively parallel simulation code used in cosmology, galaxy formation and planetary science. The project will establish a portable and maintainable framework for accelerating SWIFT’s different physics modules on GPUs and will support adoption through workshops, training and hands-on assistance for users and contributors.
Links: SWIFT website | SWIFT repository
Domain: Astrophysics, cosmology and planetary science.
Team: Levi John Wolf, Project Lead (University of Bristol); Martin Fleischmann, International Project Co-Lead (Charles University); and Joris van den Bossche, Specialist (independent contractor).
Description: GeoMUSES will strengthen the Python software ecosystem used for spatial analysis in urban social and environmental research. The project will complete the transition from the unmaintained pandana package to its successor, pandarm, integrate this work with GeoPandas and PySAL, and develop practical documentation and training for users and contributors.
Links: GeoPandas | PySAL | GeoPandas repository | PySAL repositories | pandarm repository
Domain: Geospatial analysis, urban studies, and environmental science.
Team: Franck Patrick Vidal, Project Lead; Edoardo Pasca, Project Co-Lead; and Nalin Gupta, Research Software Engineer (UKRI-STFC Scientific Computing).
Description: gVirtualXray is an open-source library for simulating X-ray imaging across research, education and industry. The project will migrate it from OpenGL to the modern Vulkan graphics API, improving performance, energy efficiency and hardware compatibility while strengthening documentation, testing and community coordination.
Links: gVirtualXray website | gVirtualXray source code
Domain: Computational X-ray imaging, medical imaging and non-destructive testing.
Team: Stephen Thomson, Project Lead; William Seviour, Neil Lewis and Geoffrey Vallis, Project Co-Leads; and Daniel Williams, Research and Innovation Associate (University of Exeter).
Description: Isca is a flexible climate-modelling framework used to investigate the atmospheres of the Earth and other planets at different levels of complexity. The project will establish reliable cross-platform installation routes, integrate developments from community forks, strengthen automated testing, and formalise governance, release and contribution processes.
Links: Isca website | Isca repository
Domain: Climate modelling, atmospheric science and planetary science.
Team: Peter Freeman, Project Lead; John Wagstaff, Research and Innovation Associate; and Steph Massey, Grant Manager (University of Manchester). Ivo Fokkema, International Project Co-Lead (Leiden University Medical Centre).
Description: VariantValidator, the Leiden Open Variation Database and the LOVD HGVS Syntax Checker help ensure that genomic variants are represented accurately and consistently across research, diagnostics and publishing. The project will reduce technical debt, improve interoperability and documentation, and establish stronger governance and sustainability structures.
Links: VariantValidator | VariantValidator API | VariantValidator repositories | LOVD | LOVD repositories | LOVD HGVS Syntax Checker
Domain: Genomics, clinical diagnostics and genetic-variant validation.
Team: Faisal Mushtaq, Project Lead; Dominik Welke and Matthew Warburton, Research and Innovation Associates; Layla Kouara, Research Software Engineer; and Cassandra Gould van Praag, Specialist (University of Leeds/Research Community Management Cooperative). Daniel Brady, Research Software Engineer (University of Sheffield). Alan Evans, International Project Co-Lead, Christine Rogers, Specialist, and Jefferson Casimir and Tyler Collins, Research Software Engineers (McGill University).
Description: This project supports an interoperable ecosystem of tools for managing, preparing, validating, analysing and sharing electroencephalography data. It will reduce technical debt, align components with evolving Brain Imaging Data Structure standards and improve annotation and validation workflows, helping researchers produce scalable, reproducible and AI-ready EEG datasets.
Links: LORIS | PyLossless documentation | LORIS repository | BIDS Python validator | EEG2BIDS | PyLossless | EEGStudyFlow | EEGNet | EEG101
Domain: Neuroscience, electroencephalography (EEG) and brain-data research.
Team: Gavin Tabor, Project Lead, and Liam Berrisford, Research Software Engineer (University of Exeter). Jony Castagna, Project Co-Lead, and Mayank Kumar, Research Software Engineer (STFC).
Description: OpenFOAM is one of the world’s most widely used platforms for computational fluid dynamics. The project will turn its emerging GPU capability into a robust, maintainable pathway by unifying CPU and GPU code, extending multi-GPU support, and developing documentation, training and community contribution routes.
Links: OpenFOAM website | OpenFOAM repository
Domain: Computational fluid dynamics, engineering and high-performance computing.
Team: Micaela Matta, Project Lead (King’s College London), and Jenna Swarthout-Goddard, International Project Co-Lead (NumFOCUS).
Description: MDAnalysis is an open-source Python library that enables researchers to analyse the large datasets generated through molecular simulations. The project will provide dedicated software engineering and community-management capacity to maintain releases and dependencies, improve testing and documentation, support interoperability, and train future contributors and maintainers.
Links: MDAnalysis website | MDAnalysis repository
Domain: Molecular simulation, computational chemistry and structural biology.
Team: Sylvain Laizet, Project Lead; Irufan Ahmed, Project Co-Lead; and Kaan Olgu, Research and Innovation Associate (Imperial College London). Shrey Bhardwaj, Specialist (EPCC, University of Edinburgh).
Description: Xcompact3D is a computational fluid-dynamics framework used for turbulence research, wind energy, aviation, heat transfer and environmental flows. The project will complete its next-generation GPU-capable solver, adding AMD GPU support, production testing, documented examples, migration tools and governance for adoption on future UK computing infrastructure.
Links: Xcompact3D website | x3d2 repository
Domain: Computational fluid dynamics, turbulence modelling, and high-performance computing.
Team: Gethin Rees, Project Lead (King’s College London); Elton Barker, Project Co-Lead (Open University); and Sarah Middle, Project Co-Lead (Archaeology Data Service, University of York).
Description: Peripleo is an open-source web-mapping tool designed for humanities and heritage research. The project will rebuild it as an accessible, browser-based application that can be configured without coding or hosting costs, supported by improved data-preparation tools, research-specific mapping features, and community governance.
Links: Peripleo demonstration | British Library Peripleo repository | Locolligo | Pelagios Peripleo repositories
Domain: Digital humanities, cultural heritage, archaeology, and historical mapping.
Team: Tasos Varoudis, Project Lead, and Alan Penn, Project Co-Lead (University College London). Nick “Sheep” Dalton, Project Co-Lead (Northumbria University). A Research Software Engineer will be recruited at University College London.
Description: depthmapX is an open-source spatial network analysis tool used to examine how the layout of buildings, streets and cities influences movement, visibility and social activity. The project will migrate it to Qt6, add modern geospatial formats and Python integration, improve accessibility and establish stronger contribution and governance arrangements.
Links: depthmapX website | depthmapX repository
Domain: Architecture, urban studies and spatial network analysis.
Team: TBC, Project Lead; Sangeeta Bhatia and Daniela Olivera Mesa, Specialists; and Mantra Kusumgar and Emma Russell, Research Software Engineers (Imperial College London).
Description: ODM is a connected set of R packages used to build, run and evaluate infectious-disease models. The project will consolidate overlapping components, expand automated testing and improve documentation, contribution processes and governance, creating more reliable infrastructure for routine public-health research and future emergencies.
Links: ODM website | odin repository | dust repository | monty repository
Domain: Infectious-disease modelling, epidemiology and public-health research.