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and its applications. Qualifications: Ph.D. in biomechanics, engineering, computer science, or a related discipline. Proficiency in programming languages commonly used in scientific research, such as
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implementation of citizen science initiatives, including outreach programs, sample collection protocols, IRB compliance, participant recruitment, and data return strategies Collaboration with international
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electrical engineering, biomedical engineering, computer science, medical physics, neuroscience, or a related field. While this is the preferred background, highly qualified candidates from other scientific
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University to get a letter of support. The call is open from October 1 to November 1, 2025. The application can be written in Swedish or in English. The postdoctoral studies at Stockholm University should
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safety at ORNL and DOE sites. This position resides in the Performance Engineering group in the Data and AI Systems Section in Computer Science and Mathematics division within Computing and Computational
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, Experimentation, Flow Cytometry, Immunohistochemistry (IHC), Informatics, In Vitro Assays, In Vivo Assays, Laboratory Operations, Laboratory Techniques, Molecular Biology, Omics, Python (Programming Language
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) Program (https://healthinformatics.umn.edu/natural-language-processing) at the Institute for Health informatics is a team of investigators, postdoctoral researchers, programmers, and students who work
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, Environmental Science, or a closely related field is required. Demonstrated experience in computational modeling, data analysis, or social science research relevant to environmental systems or infrastructure is
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discipline (e.g. Medical Informatics, Computer Science, Data Science, Computational Social Science, Epidemiology, Biostatistics, etc.) Strong research track record, programming, and implementation skills
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for longitudinal data analysis or large language models. Strong motivation in the development and application of digital twins, particularly in health and biomedical contexts. Strong computer programming skills