The beginning of the 21st century has seen enormous advances in science and technology. With the completion of the Human Genome Project and implementation of multiple “Big Data” approaches in biomedical sciences, there is now a pressing need to train a new generation of mathematically-minded biomedical scientists who will be able to bridge the gap between life sciences and mathematics/physics/informatics, and efficiently link modern biomedical research with big data research technologies. To address this need a pioneering Cross-Disciplinary Post-Doctoral Fellowships (XDF) Programme has been initiated at the University of Edinburgh in 2018 with matching financial support from the Medical Research Council. Subsequently, the XDF Programme expanded to accommodate Fellows funded from additional sources (e.g. CRUK Brain Tumour Centre of Excellence award).
The University of Edinburgh is one of the world leading research universities (ranked 4th in UK for its research power) and is at the forefront of both computational sciences and health sciences. Informatics is the largest and strongest computer science department in the UK (1st for research power according to REF2014 and REF2021), with particular strengths in data science and computational biology. Clinical medicine has been ranked 4th in the UK (research power) with the Institute of Genetics and Cancer (IGC; formerly the Institute of Genetics and Molecular Medicine) being one of the biggest biomedical research establishments in the country. The XDF Programme lead, Professor Ponting, was trained first in particle physics before pursuing a successful career in biomedicine, so knows first-hand the skills necessary for Fellows to transition into “Big Data Biomedicine”. The Programme is led by a Board of Directors, including investigators from the Institute of Genetics and Cancer and the School of Informatics, who provide Fellows with diverse perspectives.
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.
Fellows receive mentorship from both computational and biomedical scientists, and can use office space in both Informatics and IGC. Where appropriate, the research may also be conducted in collaboration with an industrial partner and/or the NHS. After their initial year, fellows focus on original research and produce material for peer-reviewed publications and for dissemination at national and international level.