27 machine-learning-postdoc Postdoctoral positions at Northeastern University in Ireland-University-Ranking-2024
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both theoretical progress and practical implementation in communication networks. Through these efforts, the Postdoc will generate impactful academic contributions that support the design of next
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genetically diverse mice under a multitude of conditions, and (3) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing
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) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing spontaneous versus precipitated withdrawal episodes. The spontaneous vs
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, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing multiscale simulation methods for quantum mechanical
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About the Opportunity Job Summary The Shansky Lab is seeking a full-time postdoc to conduct National Institutes of Health (NIH)-funded behavioral neuroscience research investigating sex differences
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, please contact Calina Copos ([email protected]). Please use “Postdoc Ad” in the subject line of all correspondence. Key Responsibilities: Assisting in initiating, executing, and completing clinical
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. The postdoc will join an interdisciplinary program that combines quantum sensing instrumentation, surface and interfacial chemistry, and the physics of the target systems, with current directions including
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About the Opportunity Conduct research on machine learning, control theory, and synthetic biology. The work will combine tools from dynamical systems, control theory, and the theory of algorithms
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-augmented generation (RAG) approaches Systems and mathematical modeling of biological or complex systems Natural language processing and machine learning Data harmonization and integration Record of research
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autonomous, closed-loop (“self-driving”) laboratory workflows. The role integrates catalyst synthesis, high-throughput reactor testing, and in situ/operando characterization with machine-learning and agentic