60 parallel-computing-numerical-methods-"Prof" Postdoctoral positions at KINGS COLLEGE LONDON
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About us: Applications are invited for a Postdoctoral Research Associate to work on the Improving Communication with Adults with Learning Disabilities (ICALD) research programme, funded by
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are looking for two highly motivated and talented postdoctoral researchers to work with Prof Craig Morgan and team on the exciting next phase of the ESRC Centre for Society and Mental Health Younger Generations
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more effective screening and therapy. The postholder will focus on developing and applying advanced computer vision and machine learning methods for multimodal imaging and real-time analysis in
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the Department of Informatics, part of the Faculty of Natural, Mathematical & Engineering Sciences (NMES). The department is internationally recognised for its contributions to robotics, AI, and human-centred
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Cardiac Therapeutics (REACT) and the BHF Centre of Research Excellence at King’s. About The Role Applications are invited for a talented and enthusiastic postdoctoral scientist to join Prof Mauro Giacca’s
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United Kingdom Application Deadline 12 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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culture models as their primary experimental system. The project will be co-supervised by Dr Ivo Lieberam (CGTRM) and Prof Juan Burrone. About the role This role is for a qualified and experienced scientist
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courses on research methods and equipment use. Strong communication skills are vital for writing up research findings, preparing materials for reports and meetings, and presenting research progress
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English Ability to work in a team Desirable criteria Numerical skills, such as: Monte Carlo methods, Density Matrix Renormalisation Group or Truncated Conformal Space Approach Knowledge of quantum field
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for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets