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being responsible for the confocal microscope (maintenance). Resources provided (equipment, IT, etc.): office equipped with a computer workstation, equipped laboratory bench, reagents and equipment shared
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). • Advanced quantitative analyses (machine learning, computer vision, multilevel statistics). • Creation and use of Python code for advanced analyses. • Management and monitoring of complex transgenic lines
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perception for robotics; machine learning. o An interest for approaches based on foundation models. o Proficiency in open-source libraries: Pytorch or equivalent, OpenCV, Open3D, PCL, etc. o Programming
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FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria We are looking for a colleague with a PhD in particle physics. Experience with machine learning and/or experience with
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. • Strong knowledge of signal processing methods and machine learning. • Familiarity with regulatory and ethical constraints in research involving sensitive data. • Ability to work closely with
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a team More specifically: - For mission 1: knowledge of signal and image processing, machine learning (PyTorch or TensorFlow + NumPy/SciPy), statistical processing & data and results visualisation
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), whose objective is to extend the HLA-Epicheck model, originally developed within the framework of a PhD thesis, and to implement new deep learning approaches to assess donor–recipient compatibility in
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of machine learning algorithms are of real interest in improving the accuracy of water quality measurements, particularly in identifying, accounting for, and neutralizing ionic interference. The second key
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, machine learning and turbulence modeling. The researcher must hold a Phd in fluid mechanics / Applied mathematic / Machine Learning. Website for additional job details https://emploi.cnrs.fr/Offres/CDD
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and AI to efficiently design safe systems. This is a postdoctoral position in the fields of AI planning, reinforcement learning (RL), and formal methods. The position is initially funded for 12 months