PhD and Fellowship Opportunities

A post-doctoral level Programme for physicists, chemists, mathematicians, statisticians, engineers, computer scientists and similar, seeking training to become leaders in Quantitative Biomedicine.

The fellowships are aimed at early-career quantitatively trained scientists, whose ambition is to achieve an independent career in data-driven computational biomedicine. Fellows follow a personalised training and research programme to become truly cross-disciplinary leaders in quantitative biomedicine. Fellows are expected to gain analytical and computational expertise, and an in-depth appreciation of biomedical and health research. They are motivated to address biomedical questions, to apply and train others in their previously acquired analytical/computational skills, and to learn the strengths and limitations of biomedical science methods. Fellows propose a well-developed, important and innovative biomedical project only after substantial relevant training.

Cross-disciplinary Fellowship (XDF) Programme homepage

Cross-disciplinary Fellowship (XDF) Programme contact

The TRAM MB-PhD scheme offers a new and exciting opportunity for bright, motivated and enthusiastic medical students to gain top quality research training during their medical degree.  The scheme is funded by the Kennedy Trust which has provided funding for a 5-year programme of joint MB-PhD studentships in Glasgow and Edinburgh as well as other UK  centres of excellence in musculoskeletal disease. 

The scheme offers students the opportunity to undertake a PhD in an area relevant to musculoskeletal disease after completion of their intercalated BSc. The scheme will also encourage graduates to follow an academic career within the area of musculoskeletal disease. The vision of TRAM is to train a future generation of academic leaders in the field of musculoskeletal disease. Successful applicants will be trained in cutting edge practical scientific and analytic skills with a focus on scientific excellence, while gaining understanding of the rigour, discipline and precision required for translational research. It is expected that the research projects will generate material that will form the basis of publications in high profile medical and scientific journals.

TRAM MB-PhD scheme homepage

TRAM MB-PhD scheme contact

The greatest challenge to realising the potential of artificial intelligence in the biomedical domain is its translation into real-world use. This programme will train graduates into a workforce with skills in computational and digital skills, and the integration of clinical, genomic, and phenotypic data. Researchers on this programme will develop technical and domain specific inter-disciplinary research skills, and gain experience delivering innovation into the public and private sectors. They will learn to successfully design, develop, and implement AI approaches in partnership with external stakeholders.

This programme is especially suitable for those with relatively little prior exposure to computer science and mathematics. This includes clinicians, allied health professionals, and biological/biomedical scientists. Our graduates will acquire technical skills from computer science, mathematics, and statistics, and domain knowledge from biomedical and clinical sciences. They will know how to practice responsible research innovation, adopt the best practice for minimising the risk of bias in AI, and understand the importance of model explainability for clinical use.

The research programme is organised into four thematic areas: AI for Innovation in; Biomedical Imaging, Biomedical Engineering, Biomedical & Health Informatics, and Genomic Medicine each with an expert theme leader supported by groups of at least twenty project supervisors from across the University.

UKRI Artificial Intelligence Centre for Doctoral Training in Biomedical Innovation homepage