Organisation/Company UCL Cancer Institute Department Cancer Institute Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions Research Support Positions Application Deadline 28 Oct 2026 – 15:55 (Europe/London) Country United Kingdom Type of Contract Permanent Job Status Full-time Hours Per Week 36.5 Offer Starting Date 1 Oct 2026 Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
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. https://www.ucl.ac.uk/cancer/.
We are seeking a highly motivated and talentedSenior Research Fellow in Software Developmentto 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 a novel neurosymbolic AI platform 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.
You will hold a PhD in Computer Science, Software Engineering, Machine Learning, Mathematics, Physics or a related quantitative discipline, with a strong track record in software development and/or research. You have extensive experience designing, building and maintaining robust, scalable software systems, and are proficient in modern software engineering practices, including version control, automated testing, documentation and CI/CD workflows.
You have experience developing and deploying AI-enabled applications, including machine learning, large language models and generative AI technologies, and are comfortable working with cloud platforms, distributed computing environments and data-intensive systems. You are an analytical problem-solver with excellent communication skills, able to explain complex technical concepts to both specialist and non-specialist audiences.
Most importantly, you thrive in collaborative, multidisciplinary environments and are motivated by the opportunity to develop trustworthy, transparent AI technologies with real-world impact. You bring a proactive approach, a commitment to technical excellence and reproducibility, and a genuine enthusiasm for working at the intersection of artificial intelligence, software engineering and cancer research.
Specific Requirements
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 and fine-tuning 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 research software development engineer (RSDE) who is passionate about applying cutting-edge formal verification and AI technologies to challenging real-world problems in biomedicine. The position offers the chance to work at the forefront of trustworthy neurosymbolic AI, formal 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.
Appointment at Grade 8 is contingent on the candidate’s previous experience.
The position is available from 1st October 2026, and early availability would be advantageous.
Interviews will be held in November 2026.
This post is funded for 3 years in the first instance, with a probationary period of 9 months.
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