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Field
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We are pleased to announce PhD studentship project in “Advanced Composites Development for Hyper-velocity Impact Protection of Space Satellites Structures”. This is an exciting PhD research
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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. Although the development of thermodynamically stable inhibitors is possible, this typically comes at a price of increased toxicity and reduced bio-degradability. Due to the ever-tightening legislation
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This research aims to develop an innovative framework that integrates health-seeking behaviour—the actions individuals take when they perceive a health problem, grounded in behavioural theories
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computational and experimental fluid dynamics in addition to product development. This project falls within the field of fluid dynamics, a discipline central to improving the efficiency of systems that involve
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experience with programming tools such as R or Python. An interest in acquiring new data science and programming skills is required. A keen interest in teaching and academic development. An excellent academic
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seek to attract, develop, and retain colleagues with diverse backgrounds and perspectives. We welcome applications from all genders/gender identities, Black, Asian, or Minority Ethnic backgrounds
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turbulence, and use this knowledge to identify control strategies through deep reinforcement learning. The methods developed in this project will directly contribute to designing novel porous media
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; Documenting dataset provenance and performing simple quality control checks; Prepare a Zenodo release with FAIR compliant metadata; Draft sections (e.g. “data description” and “technical validation”) of a
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geometries while delivering graded biomechanical support for key tasks like pinching, grasping, and extension. The PhD student will work on two key objectives: 1. Develop a novel method to link the geometry