166 machine-learning-"https:"-"https:"-"https:"-"CEA-Saclay" Postdoctoral positions in United Kingdom
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-processing system IMPROVER for blending probabilistic weather forecasts. The project will assess whether incorporating AI outputs and machine learning-based blending methods can enhance forecast accuracy
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the scientific investigation of artworks and historical objects. The project aims to advance the mathematical foundations of imaging and machine learning while directly supporting research in art history
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conferences in machine learning, statistics, and communications. Presenting research findings at project meetings, workshops, and international conferences. Supporting the supervision of PhD students and
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About the role We invite applications for a Postdoctoral Research Assistant to be part of a new research project ‘Innate and Learned Proficiencies in Facial Age Estimation’. The project is funded by
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pandemic risk policy and practice. The PDRA will drive a research project within the centre focussed on the application of machine learning and bioinformatics approaches to the prediction of pandemic risks
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To undertake research on the evolution of prokaryotic pangenomes using machine learning and AI approaches. The work will involve the analysis of large prokaryotic genome datasets, the development
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in probability, stochastic analysis, and optimization. Applicants with knowledge in machine learning, as well as a track record of publications in top Actuarial Science, Mathematical Finance
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innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a complete in silico framework to accelerate the discovery
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innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a complete in silico framework to accelerate the discovery
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-in-cell computer codes hosted on local and national high-performance computing clusters; establishing all-optical diagnostics to map temperature evolution in plasma accelerators; exploring novel inter