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of economics, programming in MATLAB and JULIA, and the Health and Retirement Study data is necessary. Understanding linkages with administrative medical records is also highly valuable. The successful candidate
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of Edinburgh and Glasgow, with expertise across computer science, wearable computing, AI and criminology. Our programme of research utilises both experimental and literature-based approaches to explore
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and leading a programme of numerical simulations relating to all aspects of our research on P-MoPAs; using particle-in-cell computer codes hosted on local and national high-performance computing
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. Engage in professional development through relevant training programs aligned with project needs and personal aspirations. Assist with the supervision of student project work and provide day-to-day support
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will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and help supervise associated PhD students. The successful candidates will join large, supportive
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Bachelor's and Master's programs and for participation in university committees What we offer: Work-life balance: Our employees enjoy flexible working hours and can partially work remotely (upon agreement
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of nitrides, along with Raman spectroscopy measurements. This programme of research will be conducted in collaboration with researchers from the University of Bayreuth (Germany), the Commissariat à l’Énergie
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Banking. Your skills and attributes for success: Expertise in one or more of the following areas: Machine Learning, Reinforcement Learning, or LLM orchestration. Strong programming skills in Python and
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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with
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for future research collaboration. To plan and manage own research activity, research resources in collaboration with others and contribute to the planning of research projects. To deliver training in research