Research Fellow / Senior Research Fellow in Artificial Intelligence for Cancer Digital Twins Full-time

Research Fellow / Senior Research Fellow in Artificial Intelligence for Cancer Digital Twins

This post is based in Professor Jasmin Fisher's laboratory at the UCL Cancer Institute. The UCL Cancer Institute is a world-leading centre for cancer research, bringing together more than 400 scientists and clinicians who work collaboratively to understand cancer and translate discoveries into improved diagnostics, treatments and patient outcomes.

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.

Cancer is a complex, multi-scale disease involving interacting processes across the molecular, cellular, tissue and organ levels. At the same time, advances in genomics, molecular profiling, pathology, imaging and clinical data collection have generated unprecedented volumes of multimodal cancer data. A major challenge is to integrate these diverse data sources into coherent computational frameworks that can generate biological insights, support clinical decision-making and accelerate therapeutic discovery.

The Fisher laboratory addresses this challenge through the development of tumour digital twins, which are executable mechanistic models that capture the biological behaviour of individual tumours and can be used to predict disease progression and treatment response. A central goal of the programme is to develop novel neurosymbolic AI methodologies that combine the power of large language models, and machine learning with formal reasoning, mechanistic modelling and formal verification to automatically construct and validate transparent, interpretable biologically grounded models directly from large-scale cancer datasets and scientific knowledge.

About the role

The successful candidate will play a central role in the design and development of a neurosymbolic AI platform for cancer. They will contribute to the integration and analysis of large-scale multi-omics and clinical cancer datasets, the development of AI models and the creation of explainable and verifiable computational frameworks for tumour digital twins. Working at the intersection of artificial intelligence, formal methods and cancer research, the postholder will collaborate closely also with Professor Mateja Jamnik and her group in the Department of Computer Science and Technology at University of Cambridge, alongside biologists, clinicians and computer scientists from partner organisations.

The research will contribute to fundamental advances in our understanding of cancer biology while supporting the development of innovative approaches for patient stratification, therapeutic target discovery, treatment optimisation and precision oncology. The successful candidate will have the opportunity to publish in leading journals, present their work at major international conferences and contribute to the development of transformative AI technologies with significant scientific and clinical impact.

This is an exceptional opportunity for an ambitious AI researcher who is passionate about applying cutting-edge AI technologies to challenging real-world problems in biomedicine. The position offers the chance to work at the forefront of trustworthy AI, neurosymbolic reasoning, computational biology and cancer systems medicine, within a world-leading research environment committed to scientific excellence and translational impact.

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.

This post is funded for 3 years in the first instance, with a probationary period of 9 months. The position is available from 1st October 2026, and early availability would be advantageous. Interviews will be held in September 2026. Applications should include a CV and a Cover Letter: In the Cover Letter, please provide evidence of the essential and desirable criteria in the Person Specification part of the Job Description. (By including a Cover Letter, you can leave blank the 'Why you have applied for this role' field in the application form, which is limited in the number of characters it will allow.)

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.

What we offer

As well as the exciting opportunities this role presents we also offer some great benefits some of which are below:

• 41 Days holiday (including 27 days annual leave 8 bank holiday and 6 closure days)
• Defined benefit career average revalued earnings pension scheme (CARE)
• Cycle to work scheme and season ticket loan
• On-Site nursery
• On-site gym Enhanced maternity, paternity and adoption pay
• Employee assistance programme
• Staff Support Service Discounted medical insurance

For rewards and benefits at UCL please visit:

Staff Benefits | UCL People & Culture – UCL – University College London

Our commitment to Equality, Diversity and Inclusion

As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women.

You can read more about our commitment to Equality, Diversity and Inclusion here:

Equality, Diversity & Inclusion: Think differently, do differently. | Office of the President and Provost (Equality, Diversity & Inclusion) – UCL – University College London

Available documents

• download: NEW2026_job_description_PDRA_AI_FINAL.pdf

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