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from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental
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organ-on-a-chip (OOC) models, colony picking and bioprinting). The ideal candidate should have strong expertise performing machine learning (ML), computational biology with the capability and/or
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This is a two (2) year 100% Contract position. This appointment may be extended or converted to career status based on the needs and funding of the department. The CW3E machine learning team is
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improving plant health using machine learning and artificial intelligence. Mentor(s): The mentor for this opportunity is Yulin Jia (yulin.jia@usda.gov ). If you have questions about the nature of the research
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested developing new machine learning methods for precision medicine and
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for Nuclear Research (NCBJ) is inviting applications for a position PhD student - scholarship (machine learning-driven modeling of metallic glasses) Location: Otwock - Świerk - in the outskirts of Warsaw with
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and motivated individual to pursue a PhD in the area of machine learning with focus on explainable clustering. The prospect PhD student will join a research team in KTH led by Professor Aristides Gionis
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Job Posting Title: R&D Machine Learning Engineer (Engineering Scientist Associate) ---- Hiring Department: Applied Research Laboratories ---- Position Open To: All Applicants ---- Weekly Scheduled
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The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 6 days ago
program at The Hospital for Sick Children, University of Toronto, and the Vector Institute. Our research group focuses on developing machine learning-based pipelines that leverage generative models and