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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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measurement methods. This Advanced Materials and Data Science project will develop data analysis methods for Raman spectra of commercially produced graphene, building on previous scoping work recently published
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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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Applications are invited for a funded PhD studentship, jointly supervised by Prof Andrew Dove (School of Chemistry) and Dr Mike Jenkins (School of Metallurgy and Materials) at the University
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This PhD studentship is an exciting, fully funded opportunity to work as part of an internationally renowned scientific and engineering team to develop a new innovative technology to meet and