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experience in perturbative large-scale structure modeling (LSS), in particular biased dark matter tracers, in simulated dataset analysis, as well as strong programming skills in Python and C. Familiarity with
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labelling of proteins and/or DNA; - has advanced skills in image analysis based on single molecule detection; - has experience with programming (our group mainly works in Python); - has experience in cell
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. - Hardware (opto-electronics) and software - Optical alignment - Model and biological sample imaging - Microscopy knwoledge - Optical imaging (theory and experiment) - Programming (Labview, Python/Matlab
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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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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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Information Eligibility criteria - PhD in astronomy, computer science or related fields - Proficiency with several of the following languages / programming models: C/C++, Python, CUDA, OpenMP, MPI, PyTorch
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) python programming skills, 2) understanding of the mathematical foundations and principles of Machine Learning, Linear Algebra (vectorial and matricial operations, optimization), with a particular focus on
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the Regulatory Certificaytion for animal experimentation - Python and/or Matlab programming for data analysis, a proven track record of previous achievements in this domain is needed - Ability to work in a team
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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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microscopy). - Understanding and modification of multi-sensor measurement architecture and control of multiple instruments (Bonsai, LabVIEW). - Data analysis in R and Python and creation of figures