1,734 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" positions in France
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, including machine learning and language technologies, for the integration and analysis of clinical, advanced data harmonisation, and next generation research infrastructures. You will contribute to research
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Description The overarching mission is to conduct research combining machine learning, data assimilation, and physical modeling to enhance short-term (days/weeks) forecasts of Arctic sea ice conditions. The
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ICT Services & Applications. Your role This position sits at the interface of machine learning, uncertainty quantification and computational biomechanics. You will work within the Legato group and in
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Your Privacy When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. This information might be about you, your preferences or your device and is mostly used to make the site work as you expect it to. The information does not usually...
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French National Research Institute for Agriculture, Food, and the Environment (INRAE) | Montpellier, Languedoc Roussillon | France | 2 months ago
with skills in statistics and modelling through machine learning (Agronomy joint research unit, MIA joint research unit, Wageningen University & Research); (ii) national and international laboratories
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of the ERC Consolidator project AUTOMATIX (see details below), we are seeking a PhD candidate to develop machine learning approaches for constitutive modeling. Context With the advent of machine-learning (ML
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spoken and written is required. The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/ ) at Institut Pasteur, led by Laura
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. 132, no. 3, pp. 1521–1534, 2012. [6] S. Koyama, J. G. C. Ribeiro, T. Nakamura, N. Ueno, and M. Pezzoli, “Physics-informed machine learning for sound field estimation: Fundamentals, state of the art, and
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computational mechanics and scientific machine learning. The successful candidate will work on the design of hybrid, physics-informed modeling and identification frameworks for complex dissipative material
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mechanics, finite element modeling, and scientific machine learning. The RSE will contribute to the design, implementation, and maintenance of open-source software libraries that integrate phenomenological