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high fidelity models of ice crystal icing accretion and shedding, verifying tools using the wealth of unique experimental validation data generated by researchers at the Oxford Thermofluids Institute
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information. About You To be successful in this role, we are looking for candidates to have the following skills
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Associate with mathematical modelling and numerical/data analysis background to join our food system resilience project, led by University of Reading, joining a large interdisciplinary team with an excellent
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concept of remedies has evolved across different dimensions of the employment relationship in a set of different national systems (i.e. France, Greece, Poland, Sweden and the UK). Data collection and
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knowledge and tools for non-equilibrium flows for hypersonic vehicles. The research will provide unique and high-quality experimental data for expanding high temperature flows. Alongside this, the proposal
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vulnerabilities (including to security and privacy) that may be introduced when AI is used to process data from wearable devices such as ‘smart glasses’. The project involves academics from Universities
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O’Brien’s research groups at the Department of Engineering Science (Central Oxford). The post is fixed term for two years and is funded by the EPSRC. The development of large-scale quantum computers will
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/scripting (e.g., in Python, and/or R, and/or Matlab, and/or Bash script & NCO & CDO, etc.) and have demonstrable expertise in the analysis of big data, while the experience with interpretation of climate
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& NCO & CDO, etc.), and have demonstrable expertise in the analysis of big data, and the interpretation of climate/weather observations/reanalyses and model simulations. Additionally, experience with