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computational framework, integrated with deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit
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water. Clearly identified scientific objectives motivate and guide the design and development of space mission by CESBIO and monitoring tools. Missions: - Data processing, apply and tune deep-learning
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under the guidance of Prof. Ivan Nourdin. Your role Conduct research in machine learning, deep learning, and probabilistic modeling, with a focus on real-world applications Disseminate research findings
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Deep Learning-type methods. The focus will be on geodesic methods, the search for paths of minimum length according to an adapted metric, imposing for example a penalization of the curvature. In addition
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integration (including environmental sensors and eye-tracking technologies), strong machine learning and deep learning skills (especially embedding models and spatial data analysis), and experience in
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Send your CV along with a motivation letter to chloe.lehoucq@pasteur.fr with benjamin.devauchelle@pasteur.fr in Cc. The candidate should have a PhD in Neuroscience or Cognitive science and the