Senior Research Fellow in Neurosymbolic AI for Cancer Digital Twins
Develop cutting-edge AI platforms for cancer research by integrating machine learning, formal verification, and biomedical data.
Best for:Best for experienced software engineers and AI researchers with expertise in neurosymbolic AI, formal verification, and biomedical data integration, seeking to impact cancer research through cutting-edge technology.
Overview
This position at UCL’s Cancer Institute offers an opportunity to advance cancer research through the creation of transparent, interpretable AI-driven digital tumour twins. The successful candidate will work within Professor Jasmin Fisher’s laboratory, designing and implementing a neurosymbolic AI platform. The role involves integrating large-scale multi-omics and clinical datasets, developing AI models, and ensuring computational frameworks are explainable and verifiable. Ideal for experienced researchers with a strong background in software engineering, AI, and biomedical applications, this position bridges computational and biomedical sciences to transform precision oncology.
What you'll do
- Design and develop a neurosymbolic AI platform for generating digital tumour twins in cancer research.
- Integrate and analyze large-scale multi-omics and clinical cancer datasets.
- Develop and fine-tune AI models for explainable and verifiable computational frameworks.
- Collaborate with multidisciplinary teams to ensure the AI technologies are transparent and trustworthy.
- Contribute to the advancement of precision oncology through AI-driven insights.
- Maintain robust, scalable software systems with modern engineering practices, including version control, automated testing, and CI/CD workflows.
Requirements
Degree required: PhD in Computer Science, Software Engineering, Machine Learning, Mathematics, Physics, or a related quantitative discipline (PhD not yet awarded may be appointed initially at Research Assistant Grade 6B with progression upon PhD completion).
Language: English (proficiency at a level suitable for academic research and collaboration)
Instruction: English
- Extensive experience designing, building, and maintaining robust, scalable software systems.
- Proficient in modern software engineering practices, including version control, automated testing, documentation, and CI/CD workflows.
- Experience developing and deploying AI-enabled applications, including machine learning, large language models, and generative AI technologies.
- Familiarity with cloud platforms, distributed computing environments, and data-intensive systems.
- Strong analytical problem-solving skills and ability to explain complex technical concepts to both specialist and non-specialist audiences.
- No explicit nationality or residency restrictions mentioned.
- Appointment at Grade 8 is contingent on previous experience.
Funding & terms
How to apply
Deadline: 2026-10-22
Applicants must submit a CV and a cover letter. The cover letter should provide evidence of meeting the essential and desirable criteria outlined in the job description. The application can be submitted through the UCL jobs portal.
- CV
- Cover letter (evidence of meeting essential and desirable criteria)
Contact
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