Ben Glocker

Imperial College London is advertising a fully funded PhD studentship in BioMedIA / Team MIRA within Imperial College Computing, as part of the UKRI AI for Healthcare Centres (AI4Health) and co-funded by GSK . The project focuses on counterfactual image generation in healthcare , with an emphasis on developing concept-driven generative models that work without explicit causal annotations. The research will explore how to leverage large language models and vision models to build concept dictionaries for medical imaging and to develop the next generation of causal generative foundation models . The studentship offers hands-on work with large-scale open datasets and supervision from an experienced team including Ben Glocker , with industry collaborators Jessica Schrouff and Xiaodan Xing . Applicants should have a background in Computer Science, Machine Learning, or AI , with strong deep learning and Python skills. Backgrounds in engineering, mathematics, or physics with strong data-analysis skills are also welcome. Prior medical imaging experience is a plus but not required. Funding is fully funded for Home (UK) students and includes tuition fees , a tax-free stipend for 3.5–4 years , and conference travel support (e.g. MICCAI, NeurIPS). There is no explicit deadline stated in the post; the position is advertised as starting as soon as possible . Interested candidates should review the programme details and apply via the AI4Health application portal.

Imperial College London’s BioMedIA Team MIRA is advertising a fully funded PhD studentship in the AI for Healthcare Centres (AI4Health), co-funded by industry partner Heartflow . The project focuses on vision-language and geometry-language models for grounded report generation from cardiac CT . The research aims to fuse 2D images , 3D volumes , and geometric structures such as centerlines and meshes to build clinically grounded, explainable systems that can generate reports and answer questions about coronary CT angiography scans, with each finding linked back to precise anatomy. Students will work with large-scale open datasets including MIMIC-CXR , PadChest-GR , CT-RATE , and RadGenome-ChestCT , and will gain experience in medical imaging , machine learning , computer vision , deep learning , and Python . Supervision is by Ben Glocker , Dr Chen Qin , Dr Wenjia Bai , and Dr Matthew Sinclair (Heartflow). Eligibility highlights: applicants should have a background in CS, ML, or AI ; engineering, maths, or physics backgrounds with strong data-analysis skills are also welcome. Prior medical imaging experience is helpful but not required. Funding: fully funded for Home (UK) students , including tuition and a tax-free stipend of at least £23,805 per year for 3.5–4 years, plus conference travel support. A limited number of overseas studentships are available for international applicants. Start date: October 2026 . Apply via the AI4Health portal and review the programme details before submitting.