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Assistant Professor position in Computer Science with a Focus on Interdisciplinary Data Science_3...
enable advanced analytics across disciplines. Experience in developing and deploying machine learning solutions is considered an advantage. Experience applying such solutions within digital humanities
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symbiosis of cutting-edge AI combined with human support. About the role The Research Scientist in Machine Learning for Wearables will develop predictive deep learning models to assess maternal and partner
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Universitätsklinikum Heidelberg – UK Mannheim GmbH | Mannheim, Baden W rttemberg | Germany | 3 days ago
and machine learning methods applied to biological data Experience working with multiomics data integration is a plus Excellent organizatorial skills, strong commitment, motivation and ability to work
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Internal Number: 7071018 Postdoc Research Associate Job Identification: 20071 Posting Date: 04/09/2026, 08:03 PM Job Schedule: Full time Locations: 101 Bagby Avenue, Waco, TX, 76706, US Degree Level: Job
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, microbes will be identified that affect fermentation outcomes. Building on previous work from the host group (doi:10.1016/j.chom.2023.05.024; doi:10.1093/nar/gkaf1388), we will develop machine learning tools
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop probabilistic deep learning models
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about advancing Machine Learning by integrating
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. Nature Biotechnology 2019, 37, 555. Genomics; Epigenetics; Transcriptomics; DNA methylation; Bioinformatics; Sequencing; Machine learning; Reference materials; Precision medicine; Data science; Artificial
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The Opportunity: We invite applications for a Postdoctoral Research Associate in machine learning based in the School of Informatics, University of Edinburgh. The postholder will also be formally
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Packages address phenotyping, plant ecophysiology, data science, and agro-economic assessments with four doctoral students, two postdocs and several technicians assigned to those work packages. The postdoc