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- l'institut du thorax, INSERM, CNRS, Nantes Université
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fellow will carry out the development of theoretical and methodological formalisms in relativistic quantum chemistry, as well as their implementation (Python). The position is within the BRUNCH project
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to compute the predicted ZTs via first principles calculations. - Computer simulations: ML + DFT - Scripting (Python) - Analysis of the results + writing publications - The position is part of an ANR-DFG
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tasks Development and implementation of behavioral protocols Analysis of imaging data Programming analysis tools (Python/Matlab) Associated activities: Participation in team meetings and seminars
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algorithms. The post-doc will carry out theoretical work on causal abstraction and causal alignment, implement algorithms and experimental pipelines in Python/PyTorch, and run experiments on GPU clusters
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describe the neuronal and behavioral changes associated with pharmacological manipulations, through the development of scripts using software such as Python or Matlab. 1) Conduct electrophysiology
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l'institut du thorax, INSERM, CNRS, Nantes Université | Nantes, Pays de la Loire | France | 11 days ago
Python, C/C++. • Possible co-supervision of Master’s and/or PhD’s students (on a similar topic). Where to apply E-mail Florent.Autrusseau@univ-nantes.fr Requirements Research FieldComputer scienceEducation
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strong expertise in data analysis and computational methods for high-dimensional biological datasets, as well as proficiency in R and/or Python programming. Previous experience with single-cell and/or
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programming in C++ and Python. - Mandatory mastery of GPU programming (CUDA) for optimization. - Experience with Deep Learning frameworks (PyTorch). - Knowledge of the AliceVision architecture is a major asset
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), nonlinear dispersive PDEs, or cold quantum gases. Practical knowledge of at least one programming language (Python, Matlab, Julia) is expected. English : level C2 is expected. Applications must include a
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Python to process observational data. - Experience in the experimental characterisation of aerosols and analysis of field data. Cross-disciplinary skills: - Excellent scientific analysis and synthesis