Research Software Engineer

Job details:
Posted 03 March 2026, Salary Grade 7: £41,064 - £46,049 per annum, End date 31 March 2026, Location Glasgow, Job Type Research and Teaching, Reference 194019, Expiry 31 March 2026 at 22:45

Based within the University of Glasgow’s Centre for Data Science and Artificial Intelligence (AI), and working closely with Research Computing as a Service (RCaaS) teams, make a leading contribution to the creation and delivery of world changing research by applying digital and scientific expertise to provide data driven solutions which can be applied to research questions and challenges. The appointed candidates will work with the researchers and the experts at the Centre for Data Science and AI and RCaaS in order to support the research projects that contribute data driven solution to the grand challenges that are aligned with the visions of the centre and within the six key Data Science and AI areas;
Health and Life Sciences, Social Sciences and Economics, Engineering and Physical Sciences, Arts and Humanities, Innovation and Impact, and the Science of Data Science and AI.

• Collaborate with research colleagues, acting as a scientific partner to develop and maintain high-quality, well-tested software as a research tool or output, with software development projects running from multiple months to many years.
• Contribute to the identification of potential funding sources and to assist in the development of proposals to secure funding from internal and external bodies to support the Centre for Data Science and AI and RCaaS, and the research software engineering strategy and core research outputs of the University of Glasgow.
• Present, disseminate and explain the team’s work through presentations, reports and well-documented software packages.
• Develop and maintain relationships with research colleagues to lobby and evangelise for better software practices and to encourage and enhance a community of practice for research software engineering.
• Develop and deliver training to research colleagues to support the development of computational and software engineering skills in the academic community.
• Undertake knowledge transfer within the team and appropriate venues including training programmes, tutorials, hackathons and data study groups.
• Support and contribute to open research, such as by applying FAIR (findable, accessible, interoperable and reusable) principles of research data and tools, within the Centre.
• Develop and enhance the profile and reputation of self, the Centre for Data Science and AI, RCaaS, and the University of Glasgow, including establishing and sustaining a track record of making a specialist contribution to publications of international quality in high profile/quality refereed journals, enhancing the research impact in terms of economic/societal benefit, and gathering indicators of esteem.
• Contribute to the enhancement of the University’s international profile in line with the University’s Strategic Plan, World Changers Together.

• A1 Postgraduate qualification SCQF level 12 (PhD) in a related Computer Science, Engineering or STEM subject or alternatively possess the equivalent in professional qualifications and experience, with experience of personal development in a similar or related role.
• A2 Excellent knowledge of applying state-of-the-art and novel data science and AI techniques emerging from research teams and elsewhere.
• A3 Breadth and/or depth of knowledge of programming languages (including Python, R, C++, Java, Julia,
  
  C), frameworks, platforms and tools, high performance computing and cloud platforms to realise collaborators' data science and AI research at scale.
• A4 Knowledge of software development practices for research including collaborative environments with multiple access, version control, issue tracking, testing and documentation.

• B1 Knowledge of best practice approaches to support research colleagues with the use of secure high performance computing environments for advanced research.
• B2 Knowledge of scaling and optimising software to take advantage of GPU / HPC infrastructure.