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Project title: Atomistic Simulations of Surface Chemistry underpinning the Atomic-Scale Processing of Materials for AI-driven Nanoelectronics Applications Supervisor: Dr. Bora Karasulu (Assistant
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Supervisors: Prof. James Kermode (Engineering) and Dr. Thomas Hudson (Maths) Summary: Inverse problems are a general class of problems that involve calibrating the parameters of a model using
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: Computer Science, Cognitive Science, Colour Science Project start date: 1st October 2024 Supervisors (*lead): Dimitris Mylonas* (Northeastern University London) Alexandros Koliousis* (Northeastern University
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mechanical effects to the domain of 2D materials and comprise exciting new building blocks for exotic new quantum engineering. These are unique and exotic among an already fascinating materials family, with
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and promoting waste. The achievement of net zero requires that materials remain efficient and in use for longer. Therefore, means to extend the lifetime of different components in different industries
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multidisciplinary team to electrochemically characterise new cathodes for lithium-ion batteries. You should have a PhD in chemistry or materials science and a track record of electrochemical or battery research
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needs and individual circumstances. Entry requirements: Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Mathematics, Physics, Chemistry, Materials Science or
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degree or its international equivalent. We encourage applications from candidates with diverse engineering backgrounds, including Textile Science and Engineering, Materials, Chemistry, Polymer
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mechanisms, while at the macro scale, the engineering issue is to develop an efficient system for integrating these metamaterials with several engineering applications. Metamaterials derive their properties
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Psychology Doctoral Research Studentship - Colour Perception and Subjective Colour Experience (2024)
A PhD studentship is available as part of the ERC-funded project COLOURCODE’, investigating the neural basis of subjective colour experience. The PhD student will use individual differences in