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Field
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Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
Location: West Cambridge, Cambridgeshire A position exists, for a Research Assistant/Associate in Photonics Integration of Graphene and Related Materials. The aim is to develop a new class of
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researchers and postgraduate students in your team. Working closely with collaborators at the University of East London, you will integrate robust MPC algorithms with advanced coalitional control strategies
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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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reach the limit of the electrical grid connections to their sites if the transition is not done in an optimal way, an issue that will be prominent in industrial, commercial and residential areas across
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optimization. An ideal candidate is expected to have a strong interest in theoretical and innovative research. To apply. Please contact the supervisor, Dr Chao Chen - chao.chen@manchester.ac.uk . Please include
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the field of intelligent systems and AI-integrated electronics. Aiming to create sustainable electronic systems, this research will develop energy-aware computing solutions that optimize power consumption and
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design A sustainable?”) represents a currently challenging research topic that warrants extensive exploration and discussion. This PhD project aims to pioneer a transformative approach to sustainable