Dame Kathleen Ollerenshaw Fellow AI & Scientific Computing in Regulatory Science
The Faculty of Science and Engineering at the University of Manchester has invested in Early Career Researchers for many years, thereby increasing the diversity of our staff. These represent a strategic investment in outstanding researchers who will shape our future research portfolio. In 2026, we plan to appoint Dame Kathleen Ollerenshaw University Research Fellowships across the Faculty. These fellowships are fixed‑term for 5 years and serve as an excellent stepping stone toward establishing an independent research career and securing a full‑time, permanent academic position. It is therefore important that applicants discuss their applications with the candidate host departments and ensure that their teaching profile and skills align with the host departments' long‑term strategy.
In 2026, we plan to appoint Dame Kathleen Ollerenshaw University Research Fellowships aligned with FSE (e.g., in the Department of Computer Science and the Mechanical Engineering and the Department of Mechanical and Aerospace Engineering), in support of the UK Centre of Excellence on in‑silico Regulatory Science and Innovation.
The UK Centre of Excellence on in‑silico Regulatory Science and Innovation
The University of Manchester coordinates the UK Centre of Excellence on in‑silico Regulatory Science and Innovation (UK CEiRSI), a pioneering multimillion‑pound initiative. This first‑of‑its‑kind centre bridges the gap between fundamental computational breakthroughs and the safe deployment of medical innovations. As a Fellow, you will lead methodological research to transform how medical products are tested and approved globally. We are driven by clinical challenges and focused on fundamental methodological breakthroughs. Your work will position in‑silico technology as a mainstream approach to eliminating risk from future pharmaceutical and medical device innovations. You will collaborate with a world‑class network that includes the MHRA, NICE, the FDA, and leading industrial partners. Manchester’s investment in facilities provides a premier environment for interdisciplinary discovery. Join us to shape the future of regulatory science through high‑impact digital twinning and AI‑driven simulation. This role offers a unique platform to contribute to the University’s Manchester 2035 strategy and social responsibility goals. Secure your place at the heart of a global hub for computational engineering and regulatory excellence.
We are looking for outstanding candidates to undertake world‑leading methodological research in the following areas, which are translatable to regulatory science as part of the UK CEiRSI:
* Physics‑Informed Neural Operators: Pioneering surrogate models that embed fundamental conservation laws to accelerate high‑fidelity multiscale simulations for engineering and biological systems.
* Probabilistic Digital Twin Synchronisation: Developing robust Bayesian frameworks and uncertainty quantification (UQ) to bridge the reality gap between real‑world sensor data and high‑dimensional computational models.
* Geometric Deep Learning for Structural Synthesis: Leveraging Graph Neural Networks (GNNs) and manifold learning to optimise complex geometries in medical device design and advanced manufacturing.
* Verifiable AI for Regulatory Assurance: Engineering formal methods and "human‑in‑the‑loop" interpretability to provide the rigorous evidentiary standards required for in‑silico clinical trial validation.
* Differentiable Multiphysics Solvers: Integrating gradient‑based optimisation directly into fluid‑structure interaction (FSI) solvers to enable seamless end‑to‑end design synthesis and autonomous refinement.
* Privacy‑Preserving Federated Learning: Establishing secure, decentralised architectures for training predictive models on sensitive medical and industrial datasets without compromising data integrity.
Propelled by clinical challenges, defined by methodological breakthroughs. This is our bold ambition: to deliver breakthroughs in core foundational science in artificial intelligence and computational engineering that have a strong impact on patient lives. If you have an interdisciplinary mindset and are comfortable working across disciplines, this is your call. Manchester has several areas of clinical strengths. Candidates with prior experience in regulatory science relevant to respiratory, orthopaedic, or cardiovascular medical devices and imaging are particularly welcome.
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