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opportunity to contribute to cutting-edge research at the intersection of artificial intelligence, machine learning, and healthcare. The successful candidate will develop and apply advanced machine learning
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Michael Bronstein, AITHYRA Scientific Director AI and Honorary Professor of the Technical University of Vienna in collaboration with Ismail Ilkan Ceylan, expert in graph machine learning, invites
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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning
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highly interdisciplinary, integrating big data analysis, state-of-the-art machine learning models, mathematical modeling, and systems biology to elucidate the mechanisms of drug interactions in complex
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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modeling are applied. To learn more about the lab: https://www.mdanderson.org/research/departments-labs-institutes/labs/xufeng-chen-laboratory.html The incoming fellow will receive training and conduct
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group (https://bckrlab.org). We focus on high impact applications and work on knowledge-centric AI and biomedical machine learning including multi-omics integration, single cell analysis, and sequential
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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)! Tübingen has a long history of academic excellence (founded in 1477; DNA was discovered here ; linked to 11 Nobel laureates) and is an innovation center in medicine and machine learning. About Eberhard
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune