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statistical and machine learning, deep learning, chemometrics, multimodal data fusion, computer vision, uncertainty-aware modeling, stochastic control, optimization, and deployable edge-to-cloud decision
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will lead and participate in observations and data analysis across the electromagnetic spectrum, or will lead work on machine learning classification of optical transients. Applicants with previous
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, focused ion beam specimen preparation, and computer vision or machine-learning analysis of microscopy datasets. The position requires strong experimental, analytical, written, oral, and interpersonal
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. The second, led by a postdoctoral researcher, develops a framework for redefining meaningful learning in the age of AI. Building on these, you will explore ways that AI guidelines are being integrated into TU
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brain MRI analysis, statistical analyses, as well as data acquisition and machine learning. Experience with stroke and federated learning is a plus. Job ID REQ20177725Posted Date 08/05/2026 Current
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evolution. ● Experience with population genetics. ● Experience developing R packages. ● Experience applying or developing machine learning tools. ● Strong scientific writing skills. Brief
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Position Description The College of Arts & Sciences at Cornell University invites applications for a two-year postdoctoral fellowship (appointment title: Postdoctoral Associate) focused
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 7 hours ago
. Examples include: determination of high-resolution shape models using shape-from-shading or novel machine-learning methods; studies of high-resolution shape models for geophysical and geological studies
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breeding program. This requires a Ph.D. with excellent knowledge and skills in drones / UAV / UAS data collection, processing, statistical analyses, AI (machine learning, deep learning) and subsequent
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Job Title Postdoctoral Research Associate Agency Texas A&M University Department Construction Science Proposed Minimum Salary $5,833.34 monthly Job Location College Station, Texas Job Type Staff Job