Sort by
Refine Your Search
-
Listed
-
Field
-
scintillation combines excellent detection efficiency for gamma rays with high scintillation light yields and very large Stoke’s shifts of >300nm. Unlike traditional inorganic scintillators, perovskite
-
Autonomous vehicles (AVs) are advancing rapidly, yet their safety assurance remains limited by the opacity of modern AI systems. Current machine learning–based decision pipelines often function as
-
. See UKCISA for further information. Starting in October 2026. You will need to meet the minimum entry requirements for our Engineering Materials PhD programme. Candidates must meet Surrey graduate entry
-
background in physics, biophysics, biological physics, or bioengineering. This PhD project will primarily focus on experimental research, which will include data analysis and there is scope for modelling
-
modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
-
treatment processes through advanced machine learning, validated against physics-based models and experimental data. System Integration: Integrating the DTs into material and energy balance equations