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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description
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, computer simulations and experiments, both in fundamental and in more applied directions. The center works to advance the understanding of porous media by developing theories, principles, tools and methods
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of CLiPS, which focuses on the application of statistical and machine learning methods, trained on corpus data, to explain human language acquisition and processing data, and to develop automatic text
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our team. We are looking for postdoc candidates to develop and apply cutting-edge technologies in spatial transcriptomics, single-cell sequencing, machine learning, and functional genomics
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experience. Research background in decision making systems, in particular the use of different optimization, machine learning, and decision making modeling techniques for problem solving. Desire to grow
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and
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-biology-neurobiology-and-anatomy/people/xuelin-lou-phd ). Postdocs are essential to the scholarly mission of the mentor and host institution, and thus are expected to have the freedom to publish the results
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. Your main tasks will be Develop and apply machine learning techniques and statistical analyses, including novel methodology for analysis of complex polygenic traits and prediction tools for precision
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biopharmaceuticals. The research at CMB pushes the boundaries of biomolecular and bioinformatics research and engineering technologies. VIB.AI studies fundamental problems in biology by combining machine learning with