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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Postdoctoral position in accordance with
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-changing technologies. Life-changing careers. Learn more about Sandia at: https://www.sandia.gov *These benefits vary by job classification. What Your Job Will Be Like: We are seeking a Postdoctoral
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for the efficient training and fine-tuning of machine learning models. The postdoc will closely collaborate with researchers at the Dutch Language Institute (and Radboud University Nijmegen). Selection Criteria PhD
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AI / Machine learning / Computational Oncology lab:Our work is translationally focused, towards realizing our vision of developing new approaches for fast and low-cost prediction of patient response
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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in Utah to recruit multiple postdoctoral fellows to apply high throughput methods and machine/deep learning to unlock the full potential of the dark proteome. Responsibilities Scientific visionRibosome
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reproducible analysis workflows Familiarity with computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
solid academic background in polymer synthesis and electrochemistry. The candidates should be self-motivated to explore new areas of studies including AI related and machine learning fields, have evidence
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 25-Mar-26 Location: Brooklyn, NY Categories: Academic/Faculty Internal Number: 183730 POSTDOCTORAL ASSOCIATE New York
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fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro