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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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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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research to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine
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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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clinical service, appointments of trust in trade union organizations, or similar circumstances. Doctoral degree should be within bioinformatics, machine-learning, computational biology, genomics, or a
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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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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fields: AI (machine learning, big database, etc) Semiconductors
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and Fluidigm technologies at UTHSC. Qualifications PhD in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, or a related field. Strong background in machine learning, data
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of extension for three years. Tiwari lab employs cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation. In this project