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emulator to demonstrate the feasibility of the new signalling/waveform. The ideal candidate for this project would have first degree and MSc/MEng in physics, electronic and electrical engineering or a
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recruitment process. Further details about eligibility and funding can be found at: https://www.ukri.org/councils/esrc/career-and-skills-development/funding-for-postgraduate-training/eligibility-for-studentship
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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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Physics at Newcastle University hosts several active research groups in the areas of cosmology, observational astrophysics and astrophysical fluid dynamics. Available PhD projects include: Examining
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studentships are available. You will develop expertise in cutting-edge laser diagnostics or direct numerical simulation (CFD) for turbulence research. You will become expert in turbulent flow physics and will
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engineering, physics, or a closely related discipline. Candidates with a strong 2:1 degree may also be considered, as well as applicants with equivalent overseas qualifications. Applications should be submitted
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. The Materials for eXtremes (M4X) research group (https://more.bham.ac.uk/M4X/ ) investigates new alloys for extreme environments from fusion & fission reactors, to aerospace gas turbines and concentrated solar
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management, breakdown capability, conduction loss reduction, switching robustness, and reliability under extreme electrical and thermal stress. Using state-of-the-art TCAD simulation and physics-based
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these extreme events across a series of complex flows. This will entail performing high-fidelity simulations of a range of flows exhibiting extreme events, developing hybrid physics-based/machine learning