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offers a unique opportunity to work at the intersection of computational physics, neuroscience, and biomechanics, developing physics-based simulations that bridge neural circuits, muscle activity, and
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for future career development in both academia and tech. Profile Required: PhD in ML, computational neuroscience, physics, engineering, or related field Strong experience in machine learning (PyTorch
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) – presentation of results at conferences – interaction with team members and international collaborators Required skills : Degree : Master of Physics, data science, computer science, applied mathematics We expect
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significant computational component. We strongly recommend a background in machine learning and coding. Applicants with a background in areas such as computational neuroscience, reinforcement learning, or deep
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interdisciplinary research team. PhD in one of the following areas: infectious disease epidemiology, mathematics, statistics, physics, AI, computer science, population biology or a similarly quantitative discipline
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of biological samples in collaboration with partner teams. Expected profile: Physicist, engineer or computational scientist Strong motivation to work at the interface of physics/engineering/computer science and