PhD Study

Join the world-leading EPSRC Doctoral Landscape Award research in collaboration with Digital Science to revolutionize how AI is used across scientific disciplines. You will leverage NLP and Large Language Models (like Gemini) to develop new AI tools for analyzing scientific literature, bridging knowledge gaps, and accelerating research innovation in areas like health and manufacturing. This opportunity offers top-tier academic research and crucial industry experience, positioning you at the forefront of the AI revolution in science. core commitment to equity, using innovative methods to define and challenge who benefits from AI and who gets to decide what 'responsible' truly means.

Supervisors: Dr. Denis Newman-Griffis (CMI), Prof. Mike Thelwall

This EPSRC Doctoral Landscape Award at the University of Sheffield offers a world-leading research opportunity to safeguard critical civil infrastructure (like bridges) by enhancing the resilience of Structural Health Monitoring (SHM) systems. The project tackles the urgent problem of cyber-physical attacks against the AI and Machine Learning models used for maintenance. You will explore various digital and physical threat modalities, investigate vulnerabilities to adversarial machine learning, and develop mitigations to prevent system exploitation, ultimately improving public safety and securing national infrastructure.

Supervisors: Dr. Max Champneys (CMI), Dr T Rogers

This EPSRC Doctoral Landscape Award at the University of Sheffield offers a world-leading, mathematically rich opportunity to design new algorithms and theory for value-based optimal stopping problems. Inspired by biological systems, the project focuses on three computational challenges: developing novel Inverse Reinforcement Learning (IRL) algorithms to uncover hidden reward functions; conducting theoretical analysis of efficient decision policies; and creating high-performance, parallelized numerical solutions to complex Bayesian optimal stopping problems. This research is ideal for candidates with strong mathematical ability and an interest in applying control theory and AI principles to critical real-world challenges.

Supervisors: Prof James Marshall (CMI), Dr Morgan Jones (CMI)

This EPSRC Doctoral Landscape Award at the University of Sheffield offers a world-leading opportunity to ensure human safety as complex, autonomous robots operate alongside people. The project develops a revolutionary approach to robot safety by focusing on identifying the safe bounds of human and robot behaviours, rather than pre-defining every hazard. You will develop a hazard assessment methodology implemented in a digital twin of a robotic system, with support from a University spinout and the Health and Safety Executive (HSE), offering direct real-world impact on robotic safety standards.

Supervisors: Dr James Law (CMI), Dr Jonathan Aitken

Secure an EPSRC Doctoral Landscape Award at the University of Sheffield to lead innovative research into user trust in future technologies, like assistive robots. This project will develop a novel experimental paradigm that uses Generative AI (for video, images, and text) to create large-scale, personalized "design fictions" about future tech scenarios. Working with North Yorkshire Council, you will analyse public attitudes and design factors to inform the creation of inclusive and trustworthy robotic systems, gaining expertise in AI, participatory design, and statistical analysis.

Supervisors: Dr James Law (CMI), Dr Dave Cameron

This EPSRC Doctoral Landscape Award at the University of Sheffield offers a world-leading research opportunity to tackle global hypertension by pioneering a non-invasive, continuous blood pressure (BP) monitoring system. The project uses Deep Learning AI to directly analyse Photoplethysmography (PPG) signals—technology embedded in popular wearables. You will develop multimodal AI models integrating PPG with clinical data, creating a scalable solution that eliminates the need for extra sensors and makes continuous, personalized heart health monitoring an easy, everyday reality.

Supervisors: Dr Shaoxiong Sun, Prof Haiping Lu (CMI)

This EPSRC Doctoral Landscape Award at the University of Sheffield offers a world-leading opportunity to fuse Materials Science and Artificial Intelligence. The project focuses on creating fast, reliable Physics-Informed Machine Learning models to simulate magnetic quasi-particles (skyrmions), critical for next-generation computing. You will embed physical and topological constraints into advanced AI architectures to enable the high-throughput discovery and rapid prototyping of novel magnetic devices.

Supervisors: Dr Matthew Ellis, Prof Tom Hayward (CMI)

This EPSRC Doctoral Landscape Award at the University of Sheffield offers a world-leading opportunity to solve the dramatic energy consumption challenge of modern AI. The project will pioneer new neuromorphic hardware by developing the first physical implementation of Kolmogorov–Arnold Networks (KANs) using nanoscale magnetic (spintronic) materials. This research combines modelling and experimentation to enable brain-like computation with drastically lower power consumption for next-generation intelligent edge devices.

Supervisors: Dr Matthew Ellis, Prof Tom Hayward (CMI)