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high-impact publications. 2-year appointment, with potential for extension subject to performance and fund availability. Responsibilities Develop advanced statistical and machine learning modeling
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machine learning and AI techniques to improve prediction of contaminant transport, sediment dynamics, and ecosystem exposure in complex fjord environments. The research will benefit from extensive
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of boreholes, and utilizing instrumentation to observe how fire impacts water movement through the vadose zone. Learning Objectives: This summer program provides an opportunity to gain hands-on experience with
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shifts and geochemical fluxes within the vadose and groundwater zones. Learning Objectives: This summer program provides an opportunity to gain hands-on experience with Forest Service monitoring protocols
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. This project involves the development and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in the dynamics of G-protein coupled receptors to enable
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for yourself with the ability to purchase coverage for eligible dependents. Position primarily works on campus, but some remote work may be possible. Fellowship Learning Goals: To learn to function as a
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-of-the-art models for computer vision based on Machine Learning. Work plan: - Analysis and study of existing resources. - Analysis of the state of the art in universal adversarial attacks on computer vision
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: MSc degree completed. Additional optional skills and qualifications: Previous research experience, particularly in the fields of Internet of Things security and machine learning models applied
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BSL-3 and BSL-4 laboratories, learning and applying cutting-edge in vitro and in vivo techniques. Collaborate across sectors: Participate in projects involving partnerships with government, industry
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-of-the-art models for computer vision based on Machine Learning. - Analysis and Study of existing resources; - Analysis of the state of the art in adversarial attacks and adversarial training and their