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Field
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computational theory, analysis, and modeling of neuroscience data and concepts. Proposals focused on disease mechanisms or that do not contribute to our understanding of non-disease states are not suitable
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knowledge of their development and structure. Working closely with colleagues at the Universities of Leeds and Reading, you will integrate theoretical understanding, observational data, and modelling
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: Probabilistic generative models (VLMs, diffusion, flow models) Reinforcement learning & Markov decision processes Causal inference & counterfactual reasoning Mechanistic & physics-informed modeling Agentic AI
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coupling systems.; • Develop technical skills in electromagnetic modeling and simulation tools, as well as in energy efficiency optimization algorithms.; • Consolidate the ability to write scientifically and
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clearly Fluency in relevant models, techniques or methods and ability to contribute to developing new ones Ability to assess resource requirements and use resources effectively Understanding of and ability
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of national and international funding agencies, as well as from industry. Job description We are seeking an ambitious candidate to develop Machine Learning models and frameworks for time series
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projects: Collaborate flexibly with multiple research groups to investigate human cognition through computational theory, analysis, and modeling of neuroscience data and concepts. Proposals focused
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approach of microbiology, biochemistry, molecular biology, multi-omics and mathematical modelling to understanding the role of metabolic pathways in the virulence and antimicrobial susceptibility
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. The project includes collaborations with disabled musicians, and we are led by the social model of disability. Consequently, disabled researchers and those with lived experience of disability are encouraged
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; undertake advanced statistical analyses including multi-level and longitudinal modelling; publish high-quality research outputs in leading journals; collaborate on research projects and contribute