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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling
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of innovation in physical sciences, create collaborations and new avenues in life science which will lead to new therapeutics and advance our understanding of human biology. If you are a creative scientist who
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establishments (Université Côte d'Azur, CNRS, INRAE, INSERM ...), but also with the regiona economic players. With a presence in the fields of computational neuroscience and biology, data science and modeling
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2040 programme. After reaching scientific gain in laser-driven ICF experiments at the National Ignition Facility, there is a global endeavour to turn the scientific milestone into practical application
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
Sensing, Geoinformatics, or similar. We are searching for a highly motivated candidate who has: Knowledge of carbon cycling and dynamics in wetlands Knowledge and experience with working with process-based
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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Postdoctoral researcher in Environmental Analytical Chemistry, with a focus on non-target screeni...
of Environmental Science has about 150 employees working in basic and problem-oriented research within environmental science, including chemical and physical processes and interactions between environment and
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The Rantalainen group is focused on application of machine learning and AI for development and validation of predictive models for cancer precision medicine, with a particular focus computational pathology. Our