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Open PhD, Masters & Postdoc positions
PhD Studentship: Lightweight Trust-Aware Private Federated Learning for Secure UAV Swarms under Model Poisoning Attacks
- Manchester, United Kingdom
Unmanned Aerial Vehicle (UAV) swarms are becoming increasingly important for defence, emergency response, infrastructure inspection, and future autonomous systems. These swarms can use federated learning (FL), where multiple UAVs collaboratively train artificial intelligence models without sharing raw mission data. This supports privacy and efficiency, but it also creates a serious security risk: a compromised UAV may send poisoned model updates that corrupt the shared intelligence of the swarm. This PhD will develop lightweight, trust-aware methods to make FL models safer for UAV swarms. The
PhD Studentship: An adaptive AI-driven Approach to Accessibility for Visual Impairments in Games
- Manchester, United Kingdom
Artificial intelligence is creating new opportunities to make games more accessible and inclusive for everyone. This PhD project will explore how AI can support players with visual impairments by enhancing understanding, navigation, and interaction within game worlds. Potential areas include dynamic guidance systems, adaptive game content, and personalised accessibility features that respond to players’ needs in real time. The successful candidate will work with an interdisciplinary supervisory team, benefiting from expertise in adaptive systems, accessibility and human-computer interaction, a
PhD Studentship: AI-M Coast: AI-Modelling of Saltmarsh and Seagrass Vegetation for Coastal Protection
- Manchester, United Kingdom
Coastal flooding is becoming more frequent and severe due to climate change, rising sea levels, and increased storm intensity. Saltmarsh restoration, widely promoted as a nature-based solution, can reduce wave energy and flood risk while also supporting biodiversity and carbon storage. However, there is limited understanding of how effectively restored saltmarshes provide coastal protection compared with natural systems. This interdisciplinary project will combine laboratory experiments, numerical modelling, and advanced artificial intelligence (AI) techniques to improve predictions of the coa
PhD Studentship: Development of Innovative and Efficient Computational Fluid Dynamics Simulator based on Physics-Informed Neural Networks
- Manchester, United Kingdom
Despite significant advances in numerical techniques and computing hardware, the high computational cost of large-scale 3D computational fluid dynamics (CFD) modelling remains a major challenge. A new approach has emerged that integrates data and mathematical models through neural networks. This has led to the development of a method for solving partial differential equations (PDEs) known as physics-informed neural networks (PINNs). However, these approaches are still in their early stages of development and have yet to demonstrate their effectiveness for complex real engineering problems. Thi
PhD Studentship: Automated, Explainable Geological Interpretation of 3D Digital Twins Under Conceptual Uncertainty
- Manchester, United Kingdom
Can AI learn to reason like a human - and recognise when it isn’t sure? This PhD tackles that challenge in a high-impact setting: interpreting 3D digital models of rock formations built from drone and laser-scan data. These models underpin decisions impacting net-zero ambitions, yet interpretation remains slow and subjective. We need tools that make geological reasoning faster, more transparent, and more consistent. Current AI systems struggle because they assume a single correct answer, when geological evidence often supports multiple plausible interpretations; so, training AI to copy one exp
PhD Studentship: Adaptive Large Language Models for Low-Resource Languages: Bridging the Global Digital Language Divide
- Manchester, United Kingdom
This PhD asks a different question: instead of demanding more data, can we build language models that learn smarter from less? You will design AI architectures that adapt to the structure of a language, including its grammar, script and complexity, rather than to how much text happens to be available online. You will test these ideas across a diverse range of underserved languages, and work directly with speaker communities to ensure the technology is genuinely useful to them. You will gain deep expertise in machine learning and natural language processing, access to high-performance computing
PhD Studentship - Universal Layered Triple-Route Architecture for Heterogeneous Quantum-Classical Security
- Manchester, United Kingdom
Quantum computers are on the horizon that could break the encryption protecting our banks, hospitals, and national infrastructure. This fully funded, part-time PhD studentship offers the chance to help build the next generation of communication security, before that threat arrives. You’ll develop ULTRA, a novel “Trinity” security framework that combines three independent forms of protection: a quantum channel, post-quantum mathematics, and traditional classical security, into a single, unified encryption key. Crucially, the system is expected to work with the infrastructure organisations alrea
PhD Studentship - Vision Language Models for Micro-Expression Analysis
- Manchester, United Kingdom
Micro-expressions are tiny, involuntary facial movements that can occur when a person tries to hide an emotion, but are difficult to analyse because they are subtle, short-lived, and easily confused with ordinary facial movement. While many methods have been developed to recognise and localise micro-expressions, these results remain difficult to understand. The proposed models will be designed to identify where the relevant facial evidence occurs, describe what subtle change has been observed, and explain why a prediction has been made. The project will deliver new methods, benchmark protocols
PhD Studentship - Nutrition Support through Embedded Research: A Vehicle for Improving Health, Performance and Culture at GB Taekwondo
- Manchester, United Kingdom
This three-year full-time PhD project will explore nutrition in Taekwondo, a weight-category combat sport where the way athletes fuel, recover and manage weight affects both performance and long-term health. This project is a partnership between Manchester Metropolitan University’s Faculty of Health and Education and GB Taekwondo, offering the chance to shape nutrition practice in a high-performance Olympic programme ahead of Los Angeles 2028 and beyond. Working as an embedded researcher within GB Taekwondo, you will explore current nutrition practice and the views of male and female athletes
PhD Studentship - Long-distance Continuous Variable Quantum Key Distribution with Amplifiers and Memories
- Manchester, United Kingdom
Entanglement distribution is a foundational capability for quantum networks, enabling diverse quantum technologies including—but not limited to—quantum key distribution (QKD). QKD provides information-theoretic security even against quantum-capable adversaries, making it one of the most mature and commercially relevant applications of quantum communication. However, current QKD links are limited to short distances. Overcoming this limitation requires quantum repeaters, which enable long-distance entanglement distribution and are therefore essential for building large-scale, secure quantum netw