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of complex mechanisms in large biological objects. (3) Computational modeling of transition pathways in high-dimensional systems. Prior experience in computer programming, machine learning algorithms, and
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LPSM (Laboratoire de probabilité et modèles aléatoires) in Paris. Main mission : The project lies at the interface between quantitative ecology and statistical learning. It brings together the expertise
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The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, headed by Laura Cantini, works at
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Context Recent advances in computer vision and generative AI have enabled major breakthroughs in image and video understanding. However, modern deep learning models remain critically dependent
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/recruitment/2-year-postdoctoral-p… ** Project ** Computational and high field MRI characterization of learning and decision-making ** Supervisor and contact ** Dr Florent MEYNIEL https://www.unicog.org/lab
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. This Post Doctoral position is part of the SilentPitch ANR project which involves a puri-disciplinary team of researchers including machine learning, speech science, cognition and behavioural studies
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ANR project which involves a puri-disciplinary team of researchers including machine learning, speech science, cognition and behavioural studies. This Post Doctoral position will be co-supervised by
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, the ability to analyze the full dataset collected by the experiment will be severely limited. The L2IT is a leader in developing new track reconstruction algorithms using geometric deep learning methods
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to align neuromorphic algorithms with the physical constraints of the target hardware. This hardware–software co design effort will involve: • Deepening and extending NSS-related machine learning and
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astrophysics, cosmology, or a related field completed by the start date; strong programming skills; working knowledge of machine learning applied to astrophysics and cosmology, in particular simulation-based