Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- ; Loughborough University
- University of Nottingham
- ; University of Surrey
- ; Cranfield University
- ; University of Bristol
- ; University of Reading
- ; London South Bank University
- ; Newcastle University
- ; The University of Edinburgh
- ; University of Birmingham
- ; University of Nottingham
- AALTO UNIVERSITY
- Cranfield University
- University of Cambridge
- University of Sheffield
- 6 more »
- « less
-
Field
-
exist—such as model checking, symbolic execution, and interactive theorem proving—they are rarely applied together in a coordinated manner. This project aims to change that by introducing a rigorous
-
and regenerative medicine. This project will focus on developing patient-derived stem cell models to advance autologous cell replacement therapy for diabetes. The PhD will involve: Generating patient
-
Flooding stands as the most prevalent natural hazard. However, whilst substantial research effort has been reported in the last decade to develop high-performance physics-based models for more
-
centres on developing predictive frameworks that accurately forecast match outcomes and league positioning through sophisticated data analysis. The candidate will implement machine learning techniques
-
its use of AI-driven predictive models that analyse real-time data from IoT-enabled devices to forecast patient outcomes, such as the risk of sepsis from urinary tract infections. This proactive
-
, focusing on performance, operability, and dynamic behaviour (e.g. water hammer effects). Working closely with Rolls-Royce, your research will develop and validate models using real-world industrial data
-
PhD Studentship - Discovery of Novel Biomarkers in Rare Neuromuscular Disease Using Stem Cell Models
into the rare NMD patient registry established in the LifeArc Centre for Acceleration of Rare Disease Trial to determine if biomarkers identified from cell models correspond to biosamples from patients with rare
-
multimodal machine learning, large language models, and fairness and uncertainty evaluations. The PhD student will benefit from: State-of-the-art AI computing recourses for large-scale model training including
-
their property. Methodology: The aim is to apply a newly developed Coupled Human And Natural Systems (CHANS) model to simulate and understand the interactive human behaviours and social dynamics before and during
-
Models (LLMs). The selected candidate will work on advancing resource-efficient generative AI and multimodal LLMs, with applications across diverse domains. The project will explore innovative techniques