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of the project (patents, communications, outreach). Conducting in vivo optical imaging experiments on healthy and patient volunteers; Developing image-analysis pipelines (Python, MATLAB) and modeling functional
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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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well as time-resolved spectroscopy. Basic programming skills are welcome as the facility is currently implemented with Python. The postdoctoral researcher will work in the Materials and Light Department
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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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physics, mathematics, and statistical/AI approaches. • Proficiency in programming (mainly Fortran, Python) and the Linux/Unix environment. • Experience in high-performance computing and large datasets
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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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condensates - have practical experience in single-molecule fluorescence microscopy - have practical experience in cryogenic electron tomography - have knowledge of data processing using R, Python, or equivalent
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of computational neuroscience concepts - Expertise in dynamical systems theory - Knowledge of machine learning - Experience with neural data analysis ### Technical Skills - Advanced scientific programming (Python
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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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tasks Development and implementation of behavioral protocols Analysis of imaging data Programming analysis tools (Python/Matlab) Associated activities: Participation in team meetings and seminars