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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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materials that show limited long-range order between layers are particularly exciting because their interlayer chemistry can differ significantly from crystalline materials. This can potentially be tuned via
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In the early development of new active pharmaceutical ingredients (APIs), pharmaceutical scientists often have access to only small amounts of material for testing. Even as we move through
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materials. The project will be carried out in collaboration with the Rutherford Appleton Laboratory (RAL) of the UKRI Science & Technology Facilities Council (STFC). Scintillators are a class of luminescent
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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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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