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Postdoctoral Associate – Transdisciplinary Agroecology - CALS - Department of Global Development Postdoctoral Associate – Transdisciplinary Agroecology Seeking a postdoctoral associate with PhD
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monitoring approaches (e.g., machine learning, real-time sensing). Sponsorship / work rights forAustralia You must have unrestricted work rights in Australia for the duration of this employment to be eligible
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://postdoc.wustl.edu/prospective-postdocs-2/ . Lab website: https://cruchagalab.wustl.edu/ . Research Projects: Plasma, CSF and Brain Proteomic analysis. Biomarker identification through the use of machine learning
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 months ago
of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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programs Posting Summary The Guzmán-Vélez Lab at Rutgers University (PI: Edmarie Guzmán-Vélez, PhD) is seeking a highly motivated Postdoctoral Associate to join a multidisciplinary research program focused
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affiliates reflect strengths in machine learning, biological modeling, data ethics, data sovereignty, computer science, environmental data science, climate change policy and modeling, evolutionary genetics
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loop/TAD structures. - Perform comparative analyses versus Populus tremula; apply network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce
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. Candidates whose doctoral work focused on deep learning methods and who have a strong interest in genomics will also be considered. Experience: At least one publication in computational genomics or machine
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with members of the IPMU and Oxford groups is highly encouraged. You will have the opportunity to teach. Applicants should have a PhD (or close to completion) in Physics or a related field. Previous