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predictive modelling; Bioinformatics and Knowledge Graphs (visualization and reporting); AI-based data integration across cohorts (with federated machine learning); Contribute to ongoing projects, such as: o
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the ability to quickly learn new things and work independently, along with previous research experience in at least one of the following areas: 1) statistical genetics/genomics/omics, or 2) deep/machine
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infrastructure, with the state-of-the-art reinforcement learning and generative AI, to detect, prevent, and preemptively mitigate intelligent attacker vectors. Supportive Mentoring: The postdoc will be guided by
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at https://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty mentor including (but not limited to): Study Development: Conducting literature review, designing studies
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hardware Experience with atomic layer deposition and process development Experience with thin film and materials characterization Strong background in computational materials science and machine learning
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for a diverse population of undergraduate and graduate students from across the US and the world, as well as crisis intervention in our Wellness Exchange walk-in clinic. Postdocs also spend part of
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will continue to build from our learnings. https://pubs.rsc.org/en/content/articlelanding/2025/gc/d5gc01813g https://pubs.rsc.org/en/content/articlehtml/2018/gc/c7gc03747c https://pubs.rsc.org/en/content
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Cornell University, Electrical and Computer Engineering Position ID: Cornell-ECE-POSTDOC [#31375] Position Title: Position Type: Postdoctoral Position Location: Ithaca, New York 14853
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adaptation; reinforcement learning and inverse reinforcement learning. o Machine Learning & Intelligence, including machine learning and adaptation; deep learning; computer vision; machine intelligence
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. (Host institution: Iscte-IUL, Portugal) 2. Project title: Machine learning techniques for crosstalk mitigation and new passive optical network architectures. (Host institution: Iscte-IUL, Portugal