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Postdoctoral researcher (f_m_x) - Waves in the Inner-magnetosphere and their Effects on Radiation...
of the adverse effects of the space environment utilizing satellite observations, physics-based numerical models, machine learning, and data assimilation. Our research will help safely design and operate
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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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
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which
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, a large initiative funded by the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site
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theory, and machine learning to quantify and understand cancer biology. We are seeking a highly motivated Postdoctoral Researcher to develop new computational methods for the analysis and interpretation
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the ultimate goal to map and model human cell lineage dynamics across development, disease and aging at multiple levels of biological systems by integrating single-cell multi-omics and artificial intelligence
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and explainable hybrid Artificial Intelligence, i.e., the mix of formal knowledge representation and reasoning with sub-symbolic data-driven machine learning approaches, to work on car-driver digital
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Postdoc (f/m/d) Methods for Geochemical Exploration and Sampling Strategy / Completed PhD in the ...
# Work in an interdisciplinary team to develop analytical and statistical/machine learning methods for surface geochemical exploration # Preparation of multi-method exploration-campaigns for known deposits
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and analysis. Data analysis and interpretation, including theoretical modelling. Establishing structure-property relationships and pushing the frontiers of the field. Collaborating nationally and