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Physics (IRIS-HEP, http://iris-hep.org/), which is developing innovative solutions to the computational and data challenges of the High Luminosity Large Hadron Collider (HL-LHC), which will collect data
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demonstrated expertise in energy systems analysis, in the collection, processing, and integration of country-specific data for economy-wide energy system decarbonization models, in the production of spatially
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to participate in projects that research and refine quantitative methodology for political science. The postdoc will work on a variety of projects, which may include methods for large language models, the impact
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demonstrated expertise in energy systems analysis, in the collection, processing, and integration of country-specific data for economy-wide energy system decarbonization models, in the production of spatially
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. This work will involve: i) contributing to design and run new Large Eddy Simulation experiments; ii) and analyzing the LES output to generate training data; iii) using Machine Learning techniques to learn
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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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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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research thrusts (or both): 1.Applied operations research: scholars will develop and implement novel methods to improve the computational performance and resolution of large-scale optimization models