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CENTD, a multidisciplinary center studying molecular targets of inflammatory diseases, isoffering a postdoctoral position for 12 months. The project aims to identify and validate newpharmacological
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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro
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learning, small data learning · Active learning, Bayesian deep learning, uncertainty quantification · Graph neural networks This position involves active participation in a well-funded
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patient-derived xenograft (PDX) models to discover novel therapeutic targets and biomarkers. The postdoc will have access to state-of-the-art facilities, multidisciplinary collaborations, and opportunities
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) Experience of working with multiple stakeholders in complex systems. Experience in large scale simulations Experience in Bayesian methods Experience using CRAFTY agent based model Full details of the role and
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on engineering nanoparticles for more targeted laser therapeutics and exploring new drug discovery for pediatric high-grade gliomas using connectivity mapping. Additionally, we are actively involved in
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that can facilitate timely diagnosis and inform targeted interventions for infants vulnerable to delayed language development. The successful candidate will join a collaborative, multidisciplinary team
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and learning occurs in a recursive Bayesian process by which the brain tries to minimize the error between the input and the brain’s expectation. In particular, MIB focuses on how music is involved in
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 6 days ago
on prostate biopsies, but accurate navigation and targeting during the procedure are challenged by ultrasound imaging limitations, as well as movement or deformation of the prostate. Current clinical navigation
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow