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), multimodal vision and language models, and Large Language Models. Please find prior work here: (Google Scholar: https://scholar.google.com/citations?hl=en&user=oEifmSgAAAAJ&view_op=list_works&sortby=pubdate
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policy, economics, statistics, or a related quantitative field Additional Qualifications Strong skills in Stata, R and/or Python and experience analyzing complex data Demonstrated experience working with
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2021; Khoshkhoo et al. JAMA Neurology 2023; Farrell et al. Nature 2024; Bizzotto et al. PNAS 2025; Khoshkhoo et al. bioRxiv 2026. For more information, please check our websites at https
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into R&D projects. The following requirements will be preference factors: • Programming skills, namely in the field of the R language; • Digital skills in R, Python, SAS; • Ability to implement
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–biomolecule or catalytic system simulations Quantum mechanical methods (e.g., DFT or QM/MM) Enhanced sampling or free-energy calculations Programming or scripting for computational research (e.g., Python
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Excellent critical programming skills in Python Strong command of English (spoken and written) Familiarity with ethical and responsible AI considerations Interest in translating models into applied
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, Python, and SAS or Stata Demonstrated expertise in analysis of claims data Clear scientific writing and communication, an ability to work both independently and in teams, and a track record of publications
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communication tasks of the research results derived from the project. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for-recruitment-of-pdi-postdo… Requirements Research FieldEngineering
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demonstrated proficiency in programming, specifically in Python and R, as well as experience with modern deep learning frameworks like PyTorch or TensorFlow. In addition to technical skills, the candidate must
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
components of the role. Our UNC group is an integral part of the Triangle Universities Nuclear Laboratory (TUNL) (https://www.tunl.duke.edu/), a Department of Energy Office of Nuclear Physics Center