Blanca Rodriguez
Top university
4 months ago
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Fully Funded DPhil/PhD in AI, Computational Medicine, Cardiology and Biosciences at University of Oxford University of Oxford in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
ENAIBLE is funded by BBSRC and offers fully funded doctoral places; the post states six fully funded DPhil students per year for ENAIBLE. TTPS offers up to 8 competitive, fully funded DPhil/PhD places and includes a guaranteed three-month work placement at GSK. Funding is tied to the doctoral programmes rather than a separate scholarship name, and TTPS is jointly funded by GSK and BBSRC.
Deadline
Expired
Country
United Kingdom
University
University of Oxford
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Keywords
About this position
University of Oxford is advertising interdisciplinary doctoral opportunities for students interested in AI, computational medicine, cardiology, biomedicine, life sciences, bioscience, pharmaceutical science, machine learning, and data-driven research.
The post highlights several DPhil/PhD routes, including ENAIBLE (Enabling Next-generation AI for a Bioscience Led Economy) and TTPS (Transformative Technologies for Pharmaceutical Science), plus related doctoral opportunities in cardiovascular science and computer science.
ENAIBLE is a four-year doctoral programme led by the University of Oxford in partnership with the University of Birmingham, Aberystwyth University, and the Francis Crick Institute. It is supported by the BBSRC and leads to a DPhil at Oxford or a PhD at Birmingham or Aberystwyth. The programme prepares researchers for an AI-driven era of biology and includes interdisciplinary training, two rotation projects in Year 1, co-supervision, and a minimum three-month professional placement. The post states that ENAIBLE is recruiting six fully funded DPhil students per year.
For October 2026 entry, the post gives a deadline of 12 June 2026 and notes that this round is for home/UK students only. For October 2027 entry, programmes will be advertised in autumn, usually with deadlines in December 2026/January 2027, and scholarships will be available for both home/UK and overseas students.
TTPS is a BBSRC/GSK doctoral programme in pharmaceutical science across Oxford, Cambridge, and Southampton. It offers four years of doctoral training, intensive first-year training, two rotation projects, and a guaranteed three-month placement at GSK. The programme is described as fully funded and currently considers only applicants eligible for Home fees for 2026/7 entry.
Eligibility is interdisciplinary: applicants from Computer Science, Engineering, or Mathematics should show interest in biomedicine, cardiology, or life sciences; applicants from biomedical backgrounds should show quantitative strengths. The post encourages applicants to demonstrate genuine interdisciplinary engagement in their application.
Relevant research themes include AI for bioscience, computational biology, cardiovascular science, biomedical data science, pharmaceutical science, machine learning, and translational research. The named academic context includes Blanca Rodriguez and faculty such as Michael Bronstein, Brian Marsden, Peter Minary, Ana Namburete, Irina Voiculescu, Alfonso Bueno-Orovio, David Kay, Jonathan Whiteley, David Gavaghan, Jim Davies, and GSK-linked supervision for TTPS.
Funding details
ENAIBLE is funded by BBSRC and offers fully funded doctoral places; the post states six fully funded DPhil students per year for ENAIBLE. TTPS offers up to 8 competitive, fully funded DPhil/PhD places and includes a guaranteed three-month work placement at GSK. Funding is tied to the doctoral programmes rather than a separate scholarship name, and TTPS is jointly funded by GSK and BBSRC.
What's required
Applicants should have a background in Computer Science, Engineering, or Mathematics and demonstrate interest in Biomedicine, Cardiology, or Life Sciences; alternatively, applicants from biomedical backgrounds should show strength in quantitative approaches. The post emphasizes interdisciplinary motivation, evidence of engagement with the other field through reading, listening, or experience, and the ability to demonstrate interdisciplinarity throughout the application. TTPS also seeks candidates with a strong background in science and interest in data-driven research and computational solutions to biomedical challenges. For TTPS 2026/7 entry, only applicants eligible for Home fees are currently considered.
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Professors
Professor of Computational Medicine, Research & Innovation, Advisor & Consultant, Training & Coaching
United Kingdom
Research Interests
Cardiology
Pharmacology
Electrophysiology
Cardiac Physiology
Pharmacometrics
Professor
United Kingdom
Research Interests
Pharmacy
Pharmaceutical Chemistry
Bioethics
Bioscience
Machine Learning
ApplyKite TwinLearns as you applyMake your next move.
Prepare your application
Review drafts and confirm requirements with the university.