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of larvae recordings to learn a parameterizable generative model of larva actions with varying durations using denoising diffusion approaches on graphs. The effectiveness of this method will be validated by
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neural networks are encouraged to apply. Candidates from related fields in machine learning, applied mathematics, or physics are also welcome. Duration : We are seeking an M2 intern for a minimum duration
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both spoken and written is required The candidat must have a Master (M2) of data science, computer science, applied mathematics The position is available starting from October. Salary according
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, Applied Mathematics, or a related field. Strong foundation in computational modelling & numerical simulations The laboratory The Decision and Bayesian Computation (DBC) – Epiméthée (EPI) laboratory