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Field
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Based in the Faculty of Engineering at the University of Nottingham, this role will focus on electromagnetic design, modelling and validation of microwave heating technologies for the BioIron
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the Medical Research Council. The Research Fellow will be using Natural Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of
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individual to work on an exciting modelling and simulation project, involving extensively applied work at the intersection of software engineering research and modelling and simulation, with real-world testing
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apply the Helsinki Discrete Element Model (HiDEM) to simulations of brittle-elastic fracture, calving and retreat at Kangerlussuaq Gletsjer (KG), a large outlet glacier of the Greenland Ice Sheet. Working
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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, population-level empirical tests, and simulation modelling to explore the evolutionary roles of nutrition, reproductive investment, sexual conflict, and competition in the development of Semel parity in males
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simulation models, digitalization allows for the development of next-generation batteries by providing insights into complex internal processes, enabling manufacturers to innovate faster and adapt to growing
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datasets). Develop and apply statistical and empirical models to assess relationships between hourly precipitation characteristics and runoff. Simulate future rainfall patterns using thermodynamic scaling
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Fellow will be using Natural Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of Electronic Health Records from people
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partners. A good working knowledge of programming tools like MATLAB or Python, and familiarity with aircraft systems modelling, artificial intelligence applications, and simulation tools will be highly