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microscopy data analysis, chemometrics, and machine learning. This position is ideal for a researcher who enjoys working at the interface of imaging, data science, and environmental monitoring. The project
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of machine learning and health sciences, with unique access to experimental and clinical data. Embedded in Munich’s thriving AI landscape, fellows benefit from world-class facilities, interdisciplinary
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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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The Section of Bioinformatics, DTU Health Tech is world leading within Immunoinformatics and Machine-Learning. Currently, we, together with Lonza Cambridge, UK, are seeking a highly talented and
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bioinformatics, with a particular emphasis on performing analysis of high-dimensional data, which can be sequencing and/or imaging-based. Experience working with AI and machine learning approaches are considered a
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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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Lab ). Integrative analysis of single-cell multi-omics and spatial imaging data in cancer, immunology, organoids, etc., in the context of the Human Cell Atlas (single-cell analytics) and/or the ELLIS
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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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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, 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