Lecturer AssocProf in AI and Computational Biosciences

About us

The Division of Biosciences at UCL is a major centre for research and teaching in the biological sciences, fostering fundamental, innovative research that spans molecules to ecosystems. We are recruiting a Lecturer/Assistant Professor or Associate Professor who applies cutting-edge machine learning, artificial intelligence and related computational biology to fundamental biological problems.

About the role

To address this opportunity, CDB seeks to appoint an outstanding academic colleague who will establish an ambitious research and teaching programme applying artificial intelligence, machine learning and computational approaches to fundamental questions in cell and developmental biology.

We welcome applicants developing innovative approaches across a broad range of areas, including but not limited to machine learning, generative and foundation models for biology, digital twins, mechanistic and hybrid modelling, statistical inference, or AI-enabled experimental design. We are particularly interested in candidates whose work tightly integrates computational and experimental biology, while also welcoming researchers developing novel computational methods with broad biological applicability.

The successful candidate will establish or grow an independent, internationally competitive and collaborative research programme within CDB. They will work closely with colleagues across Biosciences and the wider university, including researchers in computer science, mathematics, engineering, health and UCL’s growing AI ecosystem.

The post holder will be expected to secure competitive research funding, supervise and mentor postgraduate researchers, and take a full part in research-led teaching across undergraduate and postgraduate programmes. They will also contribute to strategic leadership in computational and AI-driven biology across CDB and UCL.

Interview Date(s) are scheduled for: September 2026.

This appointment is subject to UCL Terms and Conditions of Service for Academic Staff. Please visit https://www.ucl.ac.uk/human-resources/policies/2021/jun/conditions-service-academic-staff for more information.

If you have any queries about the role, in the first instance please contact Professor Robert Insall () or Professor Sandip Patel (). If you need reasonable adjustments or a more accessible format to apply for this job online or have any queries about the application process, please contact the FLS HR team on

About you

You will have a PhD or equivalent qualification in computational biology, quantitative biology, computer science, applied mathematics, biophysics, engineering, statistics or a related discipline, together with an innovative research agenda that seeks to apply artificial intelligence and computational approaches to fundamental biological questions.

You will have an established track record (Grade 9) or clear potential (Grade 8) to develop an internationally recognised research programme, attract competitive external funding and contribute to interdisciplinary collaborations. You will also have experience of, or a strong commitment to, research-led teaching at undergraduate and/or postgraduate level.

You will demonstrate the ability to work across disciplinary boundaries and to translate advances in computation, machine learning and AI into new biological understanding. We particularly welcome applicants who will actively engage with colleagues across CDB and neighbouring departments specifically the Research Department of Structural and Molecular Biology and the Laboratory for Molecular Cell Biology. The expectation is to develop new interdisciplinary approaches to fundamental biological problems, and to contribute to an ambitious and collaborative academic environment.

What we offer: Visit https://www.ucl.ac.uk/work-at-ucl/reward-and-benefits to find out more.

Our commitment to Equality, Diversity, and Inclusion:

You can read more about our commitment to Equality, Diversity, and Inclusion here: https://www.ucl.ac.uk/equality-diversity-inclusion/.

Customer advert reference: B02-10646

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