This post is based in Professor Jasmin Fisher’s laboratory at the UCL Cancer Institute.
About the role
We are seeking a highly motivated and talented Senior Research Fellow in Artificial Intelligence to join an ambitious and multidisciplinary research programme focused on understanding cancer using AI to generate digital tumour twins. This programme aims to transform cancer research and precision oncology by developing a new generation of transparent, interpretable and trustworthy AI technologies that integrate machine learning, mechanistic modelling, formal verification and large-scale biomedical data.
Appointment at Grade 7 and Grade 8 is dependent upon the successful award of a PhD. Candidates who have not yet been awarded their PhD may be appointed initially at Research Assistant Grade 6B (with progression to Grade 7 and backdated salary adjustment upon submission of the final corrected PhD thesis.
Appointment at Grade 8 is contingent on the candidate’s previous experience.
For more details about the Fisher Lab, please visit: www.ucl.ac.uk/cancer/fisher-lab
This post is funded for 3 years in the first instance, with a probationary period of 9 months.
About you
You will have a PhD, or be close to completing one, in Computational Biology, Bioinformatics, Cancer Biology, Systems Biology, Genomics or a related discipline, with experience analysing large-scale biomedical datasets, including genomic, transcriptomic and multi-omics data. You will have strong programming skills in R, Python and MATLAB, alongside expertise in statistical analysis, data integration and reproducible research practices. You will be an innovative and highly motivated researcher with excellent analytical and problem-solving skills, capable of working independently while contributing effectively to a multidisciplinary team. Experience in cancer biology, computational oncology, bioinformatics or related fields is essential, and a strong publication record demonstrating high-quality research outputs is expected. You will be an excellent communicator with the ability to present complex scientific concepts to a range of audiences and collaborate effectively with biologists, clinicians, computational scientists and AI researchers. Organised, proactive and committed to scientific excellence, you will be excited by the opportunity to contribute to pioneering research at the forefront of computational cancer biology, tumour digital twins and precision medicine.
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Grade 6b - 8
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