🎓 Artificial Intelligence PhDs
You are invited to apply for a fully funded PhD investigating the intersection of artificial intelligence and software engineering. Embedded within a live venture-studio, the project explores how AI-first development re…
This PhD project addresses the challenge of data interpretation in Phased Array Ultrasonic Testing (PAUT) by investigating how Artificial Intelligence (AI) and Machine Learning (ML) can improve the reliability and consi…
PhD project at the University of Auckland applying deep learning to cardiac CT and MRI analysis. Focuses on segmentation, disease modelling, and biomarker extraction to improve diagnosis and clinical decision-making in …
Funded CDT PhD at University of Leeds using machine learning to optimise corrosion inhibitor formulations for CO₂-rich environments. Combines AI, fluidic high-throughput testing, and corrosion science to improve energy …
Fully funded PhD at University of Southampton developing next-generation in-network computing for 6G networks. Focuses on programmable networking, distributed computing, and scalable low-latency architectures for edge-c…
MSCA-funded PhD at Glasgow Caledonian University exploring sustainable futures for sports and physical activity. Combines data science, policy analysis, and climate scenario modelling to assess climate-ready interventio…
Fully funded PhD in Ireland under the SensABLATE programme, combining AI and optical imaging for real-time cancer surgery support. Focuses on intelligent imaging systems for lung cancer diagnosis and treatment guidance.
Industry-linked PhD at the University of Manchester with Honda Research Institute Europe, developing machine learning methods for high-dimensional multi-objective optimisation in complex systems like EV energy networks.
Fully funded EPSRC UDLA PhD studentships at Imperial in biomedical engineering and medicine, covering synthetic biology and cardiac imaging with interdisciplinary training and strong research support.
Fully funded 4-year PhD at Southampton’s SustAI CDT with G-Research support, focusing on AI, data science, and sustainability, with strong industry mentorship and training opportunities.
Fusion Energy, Tokamak, Machine Learning, Graph Neural Networks, High-Dimensional Data, Surrogate Modelling, Materials Science, Predictive Modelling, Dimensionality Reduction, Time-Series Analysis
This PhD focuses on developing charge-aware machine learning interatomic potentials for electrochemical applications, enabling accurate modelling of electrocatalytic systems with long-range electrostatic interactions.