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. The successful candidate will play a key role in designing and implementing research at the intersection of sensor data collection, machine learning, remote sensing, and real-time agricultural decision-making
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interpretable machine-learning models, including approaches for uncertainty quantification, model calibration, and transferability. The Postdoc will also contribute to the development of reproducible
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online learning platforms. This is an exciting position within a well-established and successful online STEM education project and a chance to make an immediate real-world impact with your work in this
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and application of advanced computed tomography methods, with a focus on photon-counting CT, quantitative image analysis, and machine learning. The position will involve work across several NIH-funded
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. Visit The Office of Postdoctoral Affairs to learn more about our postdoctoral community. Resume/CV and cover letter should be included with the online application. Stony Brook University is committed
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the state, Texas A&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about joining AgriLife
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geometry Lena Bunina Model theory, AI in mathematics, algebraic groupsmodel theory of groups, Chevalley groups, applications of AI to mathematics Shira Faigenbaum-Golovin Manifold learning, shape space
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Bryan, Texas Job Type Staff Job Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives
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substantial experience of machine learning in a research or industry environment, and have the ability and willingness to combine machine learning research with sustained engagement with historical and
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genomics, population genetics, and machine learning. The successful candidate will contribute to method development, software dissemination, and scholarly publications. Duties and Responsibilities Lead