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proposals, scientific editing, organization of scientific information, project and financial management, managing interactions with collaborators and funding agencies (i.e., preparing interim reports and
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integration with robotic platforms. -Proven experience in developing high-performance computing applications for real-time data processing. -Experience with large-scale automation projects, particularly those
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skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and software delivery f) big data visualization g) cloud computing h) web application
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; record linkage/entity resolution; data privacy techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine
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in using common programming and scripting languages to analyze or otherwise use large meteorological datasets, including numerical model output, field campaign data, reanalysis, and both remote and in
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for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to develop new AI/ML approaches for anti-doping, with a focus on
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: (a) Better design, evaluation, safety and understanding of large AI models (especially language models); (b) Applications of large AI models to many academic disciplines; and (c) Studying the impact of
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topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and computational design. Job Description We seek to hire outstanding
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on projects related to machine-learning for mass spectrometry-based metabolomics data. Positions are available starting July 2024, and will remain open until excellent fits are found. Successful candidates will
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engineering. We seek candidates with an interest in participating in large multi-PI grants and with collaborative research experiences, experience writing proposals for user-facilities, and/or experience