As it’s approaching the end of the year, it seems like a good time to look back on our most popular blog posts of 2022. What generated the most interest from the University research community this year?

Our team will be having a well earned break over the Christmas holidays!

Members of our team recently presented at a Faculty of Humanities workshop designed to raise awareness amongst their researchers of the University’s high performance computing clusters and how we could develop our services to better address their needs.

We are pleased to announce further developments of the CSF3.

Several members of our team are providing expert training for earth and environmental science researchers and PGRs in March next year. Apply now for a place!

The first meeting of the new Research IT Academic Advisory Group (RITAAG) recently took place. Find out how this group will represent all aspects of research at the University and how you can feed in your views on Research IT and research IT provision.

Adrian Harwood was appointed Head of Research Software Engineering (RSE) in Research IT in August. He has spent the last few months looking at how to take the RSE team to the next level in order to meet the growing needs of the research community here at the University.

The University has renewed the license to allow the download and install of the full suite of MATLAB products on to both staff and students’ own, or University provided, computers.

IT Services has renewed the University’s compliance with the Cyber Essentials scheme until March 2023.

Coming to the end of a fixed-term contract? Tired of being a post-doc and want to focus on developing cutting-edge software for world-leading research? Have you thought about becoming a permanent Research Software Engineer (RSE) in Research IT?

Are you a woman who uses HPC in her work and / or research? If so then join the N8 CIR Women in High Performance Computing (WHPC) chapter!

CORONET, a tool created by our Research Software Engineers (RSEs), has recently been featured in the Journal of Clinical Oncology (JCO): Clinical Cancer Informatics. Find out more about the paper’s findings which explain how the Machine Learning model was created and presented to the healthcare community.