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of Research Experience1 - 4 Additional Information Eligibility criteria We are looking for a doctor in particle physics with less than two years of experience after the PhD. Experience in machine learning and
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The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, headed by Laura Cantini, works at
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, or machine learning) Experience working with various animal models Ability to work in an interdisciplinary research environment Specific Requirements Programming experience (Python and R) Experience with
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
simulation, shape/topology and system-level design optimization applied to deformable systems — advanced level Data-driven design and modelling approaches (machine learning applied to physical/mechanical
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lie at the crossroads of multiple disciplines and involve expertise in optics, electronics, image and data processing (including machine learning), photophysics, chemistry and biology. The position is
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protocols using computer-based data collection software, preparing and submitting ethics applications, drafting informed consent documents, and pre-registering studies. - Submit research protocols
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. Interest and experience with training/fine-tuning machine learning models would also be appreciated. Interest and knowledge of economic theoretical modelling would be a plus. Strong coding skills and
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/Emissive. It will be articulated with a research engineer in computer science responsible for the computational formalization of the design space, the PhD student in psycho-ergonomics responsible for usage
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, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity
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experience in large-scale structure simulations, working knowledge of applications of machine learning techniques in cosmology and/or astrophysics (in particular simulation-based inference), strong programming