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Field
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Postdoctoral Research Associate University of Oklahoma Norman Campus: Gallogly College of Engineering: School of Aerospace and Mechanical Engineering Location University of Oklahoma, Norman Campus
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, biomedical engineering, computer science, or a closely related discipline. Certifications/Licenses Required Knowledge, Skills, and Abilities Experience with motion analysis, wearable sensors, or signal
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Computational Fluid Dynamics (CFD). This is an exciting opportunity to join a leading research group working at the intersection of AI, biomedical engineering, and cardiovascular medicine. CORE FUNCTIONS AI/ML
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. Qualifications Basic qualifications Applicants are required to have a Ph.D. in Computer Engineering, Agricultural Engineering, Data Science or a related field. Additional qualifications Experience in one or more
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of Engineering with many fascinating projects that focus on applying advanced nonlinear theoretical, computational and experimental techniques to solve practical real-world problems in engineering and biomedicine
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for Protein Design (IPD) in Seattle. The Institute for Protein Design (IPD) is creating a new world of synthetic proteins to address 21st-century challenges in medicine, energy, and technology. The IPD is a
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-immune interactions—are synchronized by gene networks, how these processes malfunction in disease, and ultimately apply this knowledge to engineer cell communication for therapeutic purposes. Required
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, and measure success. Basic Qualifications: PhD degree in a related scientific field (e.g. architecture, architectural/mechanical/electrical engineering) completed within the last five years. Proven
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, computer science, data science, social sciences, public policy, or a relevant interdisciplinary area. Interest in addressing the governance, ethical, legal, and societal implications (GELSI) posed by digital
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
quality and health risk assessments. The candidates will work on a range of tasks including: a) Perform literature review to assess current state-of-the-art in reduced form modeling approaches and assess