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-quality training and learning materials, and a sustainable plan. FSTM's main tasks are to contribute to the definition of the body of knowledge and competencies, assist in developing the skill tree used as
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Deep Learning-type methods. The focus will be on geodesic methods, the search for paths of minimum length according to an adapted metric, imposing for example a penalization of the curvature. In addition
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integration (including environmental sensors and eye-tracking technologies), strong machine learning and deep learning skills (especially embedding models and spatial data analysis), and experience in
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, Impresso - Media Monitoring of the Past (https://impresso-project.ch/ ) is an interdisciplinary research project that uses machine learning to pursue a paradigm shift in the processing, semantic enrichment
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found on hpc.uni.lu . The activities include classical HPC applications such as simulation and modeling, but also artificial intelligence and machine learning, bridging computational science, with data
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the Institute of Applied Physics in Florence, Italy (IFAC) and to conferences in Europe to present scientific results. Knowledge of inverse methods, statistics or machine learning Knowledge of remote sensing from
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(willing to learn and conduct experiment on animals), engineering, pharmacy, biochemistry or related. Engineering background is of particular interest. - Strong experience in in vivo electrophysiology and
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Postdoctoral position: Developing a human lymphoid organ-on-chip to evaluate candidate mRNA vaccines
immunology, with expertise in T cell/B cell interactions and/or vaccinology an expertise in advanced cytometry a strong motivation to learn organ-on-chip technologies a track record of publications in relevant
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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