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                science, electrical and computer engineering, sociology, public policy, information science, communication, economics, political science, psychology, philosophy, and related technology disciplines. Selected candidates 
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                to applicants with demonstrated expertise in energy systems analysis, in the collection, processing, and integration of country-specific data for economy-wide energy system decarbonization models, in 
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                application process for this position may be directed to Fiona Romaine, fromaine@princeton.edu.This position is subject to the University's background check policy. The work location for this position is in 
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                :59 pm EST) for full consideration; however, the posting will remain open until filled. Application Process - All candidates must use the online application process to submit materials at: https 
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                to ion beams with well-controlled energies and incident angles for benchmarking and validation of theoretical calculations and computational physics and chemistry modeling of important surface processes 
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                ://puwebp.princeton.edu/AcadHire/position/40561. We will begin processing applications after November 24, 2025, but applications may continue to be considered after the deadline. The Princeton School of Public and 
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                of interest include: Metabolomics, isotope tracing, metabolic flux analysis, quantitative modeling, mass spectrometry imaging, cancer metabolism, small molecule inhibitor discovery, dietary impact on cancer 
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                and institutional processes, and then incorporate them into (or couple with) global and subnational energy models to study core policy questions related to decarbonization. We welcome applications from 
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                ., or equivalent is required. Applicants should have training and a significant track record in one of the following areas: -computational biology-computer science-electrical or computer engineering-genomics 
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                , and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and computational