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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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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
, CIRAD AMAP, CIRAD PHIM, CIRAD PBVMT, INRAE ePhytia, INRAE IGEPP, INRAE LISAH, IRD EGCE, IRD IEES, Univ. Paris Saclay, TelaBotanica). This is a postdoctoral position in Machine Learning, more
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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
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of massive galaxies from the primordial Universe to z~2. This project combines a unique JWST dataset with state-of-the art hydrodynamical simulations and machine learning techniques to understand the origins
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multidisciplinary experience. Knowledge in applied computer science, particularly in machine learning; in fluid mechanics, especially in hydrodynamics; and in electronics, particularly in instrumentation and
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start quickly and effectively, leveraging your experience in data analysis, machine learning and biomarkers quantification to contribute from the onset. You will liaise with external collaborators and
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with PhD and master students and with medical doctors. You will start quickly and effectively, leveraging your experience in data analysis, machine learning and biomarkers quantification to contribute