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, or ability to learn quickly) and/or symbolic/numerical computation (Mathematica, R, Python). • Fluency in scientific English (reading, writing, speaking) is essential to interact with the project's
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-phase heterogeneous photocatalysis would be a plus - A first experience in analytics related to photocatalytic gas-phase reactions would also be a plus - Fluency in French or English, willingness to learn
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activities Your profile Master's degree in educational sciences, linguistics or psychology. A strong theoretical understanding of language learning is necessary to engage in qualitative research with education
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analytics Exploring and implementing federated learning and privacy-preserving AI approaches for distributed clinical datasets Collaborating closely with data providers, clinicians, and technical teams
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condensed matter physics • Ability to learn and develop skills in analytical computation, theoretical modelling and numerical simulations, in particular the numerical solution of partial differential
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Institut de Recherche pour le Développement (IRD) | Sete, Languedoc Roussillon | France | 9 days ago
the island food systems of the Comoros archipelago (incl. Mayotte) in order to develop an analytical framework and a model for assessing the vulnerability and resilience of these systems to climate risk. Under
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Institut National des Sciences Appliquées de Lyon | Villeurbanne, Rhone Alpes | France | 20 days ago
of an analytical model of a fluid-filled cylindrical shell and analysis of propagation modes in function of the frequency range; - selection of one ABH concept for the following of the study; - development
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applied methodologies in Data and Image Analysis, Computational Imaging, Statistical Learning, Uncertainty Quantification, Robust Estimation, and Deep Neural Networks. The group combines expertise in
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biomedical research. Your profile Master's degree in computer science or related discipline Experience with Python and recent deep learning frameworks (e.g. Pytorch, MONAI) Strong interest in image analysis
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costs and energy requirements of state-of-the-art deep learning models significantly, while democratizing them for a vast community of users, researchers, and practitioners. The task is to perform just