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with both the CNRS and UGA, organized into five research teams conducting work in cognitive science (Body and Space, Development and Learning, Language, Consciousness, Memory & Metacognition, Vision
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. The project proposes an innovative approach to model sea ice dynamics from the ice floe scale to the basin scale, leveraging hybrid data assimilation and machine learning methods to shape a physically robust
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Open Positions DC 4: Use of machine learning tools for estimating EGs performance. Host Institution University Grenoble Alpes (France) Main Supervisor Alice Di Donna (alice.di-donna@univ-grenoble
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sometimes struggle to effectively sustain patients' learning throughout their rehabilitation journey and may not adapt to the evolution of their abilities. Rehabilitation is a complex process that requires
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, a protein expressed in many cancers, which is an indispensable element of the meiotic DSB formation machinery, but which exact function is not known. In order to learn more about MEI4 and its partners
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experimental data (from ex-situ and in-situ measurement). Therefore, she/he will develop a way to optimize/guide the experiments trough artificial intelligence approach (machine/deep learning) that he will
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
Python and good analytical skills. A good background in probability/statistics and deep learning is expected. Knowledge of differential privacy and/or fairness is a plus, but not necessary. The candidate
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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore