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characterization. At SurfCat, we make extensive use of surface science techniques and collaborate closely VISION, which provides access to advanced microscopy tools. Promising catalysts may also be studied at large
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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
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or related with strong bioinformatics background) (m/f/d) with focus on the analysis of cutting-edge liquid biopsy proteomics, transcriptomics and other omics data sets related to blinding diseases, such as
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knowledge graph models of such transformations that are self-describing when applied to existing map repositories, and can be scaled up to large data repositories using state-of-the-art AI methods. In
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)function. Our approach develops methods to interpret high-performing deep learning models to distill knowledge that they learn from big, noisy biological sequence data. Our goal is to elucidate biological
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following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part
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At the University of Vienna, over 10,000 people work together on the big questions of the future. Approximately 7,500 of them are academic staff members. These are individuals who, with
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of surface chemistry, and photoelectrocatalysis. The project takes place in a large and vibrant interdisciplinary research group and will provide you with space and resources for your personal career and
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing
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in different brain models (tree shrew, macaque, human neurotypical, schizophrenia patients) and levels of analyses (local- and large-scale circuits). This is a unique opportunity to learn about team