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PhD Studentship: Towards Sustainable Powertrains: Enabling High Motor Performance without Rare Earth Materials and Energy intensive Manufacturing Processes The University of Nottingham This project
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Discover your career The world of the University of Nottingham is defined by our people and the values we share. Our environment is an ambitious vision brought to life across vibrant and forward-thinking global campuses. An ever changing world where open minds and diverse cultures are able to...
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PhD Studentship: Rolls-Royce sponsored PhD scholarship – Intelligent Mechatronics and Robotics Systems Engineering Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme...
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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PhD Studentship: Rolls-Royce Sponsored PhD Scholarship – Micromechanics and In-Depth Materials Analysis of Advanced Aerospace Materials Upon the Manufacturing Process Engineering Applications
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dealing with investigations on the development of bespoke high-tech laser beam processing methods for surface treatment and repair of aero-engine components. The project will deal with the study of a new
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new family of solid-state Additive Manufacturing technologies, such as Cold spray. The nature of the process utilising low heat input and severe plastic deformation, produces ultra-refined
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to criminal convictions will be retained confidentially and securely and access to that data will be strictly controlled. More information relating to the manner in which we process your personal data is
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with transferable expertise applicable across AI-driven domains. Application Process To apply, please send a CV, cover letter, and transcripts to Dr Christopher Wood (christopher.wood@nottingham.ac.uk
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be