King's College London is offering a fully funded PhD position in the School of Biomedical Engineering & Imaging Sciences, supervised by Associate Professor Hector Zenil and Dr Alan Hodgkinson. The project, 'AI Hospital of the Future: A Multi-Agent, Multimodal Simulation of End-to-End Automated NHS Patient Pathways,' is part of the EPSRC DRIVE-Health Centre for Doctoral Training. This interdisciplinary research opportunity focuses on developing a large-scale simulation environment for future hospitals, integrating autonomous agents, multimodal clinical data, workflow optimization, and AI-driven clinical decision pathways. The aim is to explore safe, equitable, and intelligent automation across entire patient journeys, from triage to diagnostics, treatment, and follow-up. The project will utilize rich UK health data resources, including the Clinical Practice Research Datalink and UK Biobank, to test how an AI hospital could manage real patients and potentially reduce delays or improve outcomes. Key objectives include developing specialist agents for GP triage, radiology, cardiology, neurology, and multidisciplinary decisions; building retrospective simulators to compare AI and actual outcomes; and quantifying diagnostic accuracy, time-to-diagnosis, referral appropriateness, length-of-stay, and fairness. The research will produce evidence aligned with NICE ESF and MHRA AIaMD standards to inform future NHS pilots. Applicants should have a first or upper second class degree in biosciences, computer science, mathematics, statistics, data science, chemistry, or physics, and be enthusiastic about interdisciplinary healthcare research. English language proficiency at IELTS Band D is required. International students are welcome but must cover their own visa application fees and Immigration Health Surcharge. The studentship covers full tuition fees, a tax-free stipend of £25,403.40 per year, and up to £20,000 for research consumables and conferences over four years. To apply, candidates must create an account with King’s Apply, submit an application to the EPSRC DRIVE-Health: Centre for Doctoral Training in Data-Driven Health MPhil/PhD (Full-time), and enter 'EPSRC DRIVE-Health 2026' in the funding section. A CV and a 500-word personal statement outlining motivation for postgraduate research are required. Applications close on 12 January 2026, with interviews scheduled for March/April 2026. For project-specific queries, contact the main supervisor before applying. This PhD offers the chance to join a vibrant interdisciplinary community in London, with cross-campus, cohort-based training and access to cutting-edge research in AI, healthcare automation, and biomedical engineering. The DRIVE-Health initiative is a £17M program bridging technological advances with real-world healthcare challenges, co-created with partners across the NHS, healthtech, pharma, and the third sector.

King's College London is offering a fully research-focused PhD opportunity in Computational Immunology and Digital Health, supervised by Associate Professor Hector Zenil and Adelaide De Vecchi. The project is situated at the intersection of machine learning, network science, and digital twins for healthcare, within the world-leading School of Biomedical Engineering & Imaging Sciences and the King’s Institute for Artificial Intelligence. The research will be conducted in the Algorithmic Dynamics Lab, also associated with The Francis Crick Institute. The PhD project, titled 'Algorithmic Disease Network Intervention Pipeline Using Immune Digital Blood Twins,' aims to develop a general, interpretable computational pipeline to model and influence the evolution of immune and haematological systems. By leveraging longitudinal immune data such as blood counts, symptoms, and lifestyle signals, the project will construct Immune Digital Blood Twins—dynamic models that capture transitions from immune homeostasis to early dysregulation and disease. The research combines causal inference, machine learning, deep learning, dynamical systems, and Algorithmic Information Dynamics to build disease networks from causal-temporal immune biomarkers, moving beyond black-box prediction models. The project will explore algorithmic and causal interventions to simulate clinical or lifestyle actions, studying how these may redirect disease trajectories toward healthier states. The outcome will be a versatile methodological framework advancing computational immunology, with future applications in early disease detection, personalized health monitoring, and immune system modeling. Applicants should have a strong background in Computer Science, Mathematics, Engineering, Physics, Computational Biology, or related fields. Experience with machine learning, networks, dynamical systems, or statistical modelling is desirable. Python programming is essential, and experience with deep learning and healthcare data analytics is a plus. The position is based in London, offering an exceptional academic environment next to the British Parliament. Interested candidates should contact Hector Zenil directly via LinkedIn or email [email protected]. For more information, visit the DT4Health project page and the Algorithmic Dynamics Lab website.