We are working with the new world of data driven research. Few fields have had the explosive change and adoption of big data, AI and HPC systems as much as medical and life science research. This shown by the universities recent Advanced Research Computing (ARC) and Compute and Storage for Life and environmental Sciences (CaStLeS) initiatives. The challenges faced by researchers in this field are varied. They range from scripting and programming tasks, for file format conversions to the data intensive tasks such as bioinformaticians annotations of mouse embryo gene-expression databases, to computational intensive tasks such as genomics whole genome sequence analysis, to the emerging AI fields such as computer vision for MRI scans. If this seems challenging for the researchers it is more so for research software engineers (RSE’s) in this field who have to support them via specialist knowledge in programming, secure and reliable data management, AI, statistics.
