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in a living organism, especially when the damage occurs repeatedly over a lifespan. The central hypothesis of this PhD project is that repeated temporary threshold shifts interfere with tip link repair
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in humans. The central objectives of this PhD project are to i) demonstrate that tip link rupture contributes, at least in part, to TTS in noise-exposed mice; ii) characterize the kinetics of tip link
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. The PhD (M/F), to be recruited in the context of the ERC StG MULTI-viewCELL, will be working on the development of a new method combining machine learning and biophysical modelling to model embryo
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computational reconstruction methods based on AI (deep learning) and/or compressed sensing. The envisioned imaging system will be based on a hybrid open-top light sheet microscope recently implemented in our lab
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of results at conferences interaction with team members and international collaborators Required skills : Degree : PhD in computer science, machine learning, or computational biology We expect a candidate with
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physiological function of cellular senescence, and how does it transition from a regenerative program to a driver of pathology? We investigate how senescent cells control tissue plasticity and microenvironmental
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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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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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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
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benjamin.devauchelle@pasteur.fr in Cc. The candidate should have a PhD in Human Genetics and the following skills: Strong interest in the field of genetics, neurobiology and psychiatry. Computer skills: strong level in