Dame Kathleen Ollerenshaw Fellow AI & Scientific Computing in Regulatory Science in Manchester
Dame Kathleen Ollerenshaw Fellow AI & Scientific Computing in Regulatory Science

Dame Kathleen Ollerenshaw Fellow AI & Scientific Computing in Regulatory Science in Manchester

Manchester Full-Time 40000 - 50000 ÂŁ / year (est.) No home office possible
Ellis

At a Glance

  • Tasks: Lead innovative research in AI and scientific computing for regulatory science.
  • Company: University of Manchester, a leader in interdisciplinary research and innovation.
  • Benefits: Five-year fellowship, access to cutting-edge facilities, and collaboration with top industry partners.
  • Other info: Join a global hub for excellence and contribute to impactful research.
  • Why this job: Shape the future of medical product testing and approval with groundbreaking technology.
  • Qualifications: Strong background in AI, computational engineering, and regulatory science.

The predicted salary is between 40000 - 50000 ÂŁ per year.

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 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.

Dame Kathleen Ollerenshaw Fellow AI & Scientific Computing in Regulatory Science in Manchester employer: Ellis

The University of Manchester is an exceptional employer, dedicated to fostering a diverse and inclusive work environment that champions early career researchers. With a strong focus on interdisciplinary collaboration and cutting-edge research, employees benefit from access to premier facilities and a world-class network, positioning them at the forefront of regulatory science innovation. The Dame Kathleen Ollerenshaw Fellowship offers a unique opportunity for professional growth, allowing fellows to contribute significantly to impactful research while aligning with the university's strategic goals for 2035.
Ellis

Contact Detail:

Ellis Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Dame Kathleen Ollerenshaw Fellow AI & Scientific Computing in Regulatory Science in Manchester

✨Tip Number 1

Network like a pro! Reach out to current or former fellows and faculty members at the University of Manchester. They can provide insider info on what the selection committee is really looking for, plus you might score some valuable advice on aligning your skills with their long-term strategy.

✨Tip Number 2

Get your teaching profile sorted! Make sure you can clearly articulate how your teaching experience aligns with the host departments. We want to see that you’re not just a research whiz but also someone who can inspire the next generation of scientists.

✨Tip Number 3

Show off your collaborative spirit! Highlight any past projects where you worked with industry partners or regulatory bodies. This will demonstrate that you’re ready to jump into the collaborative environment at the UK Centre of Excellence on in-silico Regulatory Science and Innovation.

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we’ve got all the resources you need to make your application shine, so don’t miss out!

We think you need these skills to ace Dame Kathleen Ollerenshaw Fellow AI & Scientific Computing in Regulatory Science in Manchester

Methodological Research
AI and Machine Learning
Computational Modelling
Physics-Informed Neural Operators
Probabilistic Digital Twin Synchronisation
Geometric Deep Learning
Graph Neural Networks (GNNs)
Verifiable AI
Formal Methods
Differentiable Multiphysics Solvers
Gradient-Based Optimisation
Privacy-Preserving Federated Learning
Interdisciplinary Collaboration
Regulatory Science Knowledge

Some tips for your application 🫡

Know Your Audience: Before you start writing, take a moment to understand who will be reading your application. Tailor your language and examples to resonate with the values and goals of the University of Manchester and the specific departments you're interested in.

Showcase Your Research Impact: Make sure to highlight how your past research aligns with the innovative work at the UK Centre of Excellence on in-silico Regulatory Science and Innovation. We want to see how your skills can contribute to transforming regulatory science and improving patient outcomes.

Align with Long-Term Strategies: Discuss your teaching profile and research interests in relation to the host departments' long-term strategies. This shows that you’re not just looking for a job, but that you’re genuinely interested in contributing to their future direction.

Apply Through Our Website: Don’t forget to submit your application through our official website! It’s the best way to ensure your application is seen by the right people and gives you a chance to showcase your enthusiasm for joining our team.

How to prepare for a job interview at Ellis

✨Know Your Research Inside Out

Make sure you can discuss your research in detail, especially how it aligns with the UK Centre of Excellence on in-silico Regulatory Science and Innovation. Be prepared to explain your methodologies and how they can transform regulatory science.

✨Align with Host Departments

Before the interview, have a chat with potential host departments to understand their long-term strategies. This will help you tailor your responses to show how your teaching profile and skills fit perfectly with their goals.

✨Showcase Interdisciplinary Collaboration

Highlight any past experiences where you've worked across different disciplines. This role is all about collaboration, so demonstrating your ability to work with diverse teams will set you apart from other candidates.

✨Prepare for Technical Questions

Expect questions related to the specific areas mentioned in the job description, like Physics-Informed Neural Operators or Verifiable AI. Brush up on these topics and be ready to discuss how your expertise can contribute to advancements in these fields.

Dame Kathleen Ollerenshaw Fellow AI & Scientific Computing in Regulatory Science in Manchester
Ellis
Location: Manchester

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