368 parallel-computing-numerical-methods-"Simons-Foundation" positions at University of Sheffield
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Research and Innovation Network. There will be the opportunity to develop models of these initiation processes in parallel with the experimental investigation. Funding Notes 1st or 2:1 degree in Engineering
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accurately collecting data with subsequent robust analysis using appropriate statistical methods. Essential Application/interview Ability to update and acquire new skills and knowledge in line with advances in
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methods. An understanding of quantitative data collection, analysis and knowledge mobilisation is desirable. In addition, you will have strong spoken and written communication skills to liaise with multiple
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including XRD, ECV, AFM, SEM, PL, Hall effect, SIMS Essential Application/Interview/Presentation Experience of designing and developing epitaxy research methods leading to high quality epitaxy results
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knowledge of coproduction and qualitative methods, and a sound understanding of key issues relating to care – including the impact of minoritisation and intersectional inequities. Understanding of survey
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Machine Learning Methods for Enhancing Autonomy of Unmanned Aerial Vehicles in Wildfire Detection and Localisation
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Artificial intelligence and machine learning methods for model discovery in the social sciences
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in 2019 and contributed to 4.95 million deaths. While the development of medicinal treatments remains an important priority, so too do other methods of fighting infections. In this project you will
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in handling stall onset and recovery. This project will focus on the modelling and control of hysteresis effects, under the framework of numerical optimal control. The aim is to develop advanced
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on complex projects using agile and waterfall methodologies with proven delivery track record. Essential Interview / Application Experience with recognised methods (e.g. TOGAF), notation standards (e.g