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POSTDOCTORAL SCHOLAR Requisition # 4657 Position Basics Advertising Ends on:Extended Until Position is Filled Advertising Started on:Friday, July 24th, 2026 College:Carver College of Medicine
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POSTDOCTORAL SCHOLAR (ARALDI LAB) Requisition # 4655 Position Basics Advertising Ends on:Friday, October 30th, 2026 Advertising Started on:Friday, July 24th, 2026 College:Carver College of Medicine
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staff position within a Research Infrastructure? No Offer Description How can institutions learn to govern technologies whose capabilities, risks and societal effects are still emerging? REGULAIRE offers
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PhD studentship: Discovery of rational therapeutic biomarkers in breast cancer by systems pathology and deep learning Supervisor: Dr Hamid Raza Ali Department/location:Cancer Research UK Cambridge
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applied mathematical modelling machine learning multi-fidelity modelling numerical methods. Demonstrated programming ability (MATLAB/Python/C++) and enthusiasm to learn PyTorch. Previous experience in one
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discipline. Essential Good programming skills, preferably in Python/C#. Experience with machine learning, deep learning, or experimental AI evaluation. Interest in secure distributed AI, federated learning
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of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research, responsible
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. POSTDOCTORAL ASSOCIATE OPPORTUNITY Acharya Lab – Division of Structural Biology The Acharya Lab in the Division of Structural Biology at the Duke Human Vaccine Institute (DHVI) is recruiting for a Postdoctoral
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and corrective feedback. You will apply advanced algorithms for machine learning, multimodal biosignal processing, and human-state inference, working with shared-control strategies and electrotactile
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
We welcome applications from candidates with a broad range of academic backgrounds and experiences for a 4-year PhD project on Mathematical and Machine Learning Aspects in Crystallography at Durham