86 engineering-computation-"https:" "https:" "https:" "https:" positions at Duke University
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COMBINATION OF RELEVANT EDUCATION AND/OR EXPERIENCE. Strongly Preferred Experiences: Thorough understanding of various engineering disciplines, including biomedical, mechanical, electrical, civil, computer, etc
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. · Excellent communication skills and ability to collaborate across diverse scientific backgrounds. · M.S., M.E. or Ph.D. in computational biology, engineering, physics, applied mathematics
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Engineering (MEng) program. The successful candidate will: Lead the Design Health Fellows Program, guiding students through clinical immersion, needs-finding, prototyping, and commercialization. Manage daily
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Occupational Summary The Quantitative Developer works with business teams and the senior developers to design and build production systems. They are responsible for building quantitative analytics
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to guide a department recognized for excellence across the environmental, structural, and computational domains of civil and environmental engineering. The successful candidate will join a dynamic community
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laundering. For more information about the QFC program in MIDS at Duke University, please see https://datascience.duke.edu/academics/electives/quantitative-finance/ Applications can be submitted online
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Master's in Interdisciplinary Data Science (MIDS) program. This is a non-regular rank faculty position to begin January 1, 2026, and finish December 31, 2026. This position is expected to teach courses
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programs to eligible team members. Learn more at: https://hr.duke.edu/benefits/ DEPARTMENTAL PREFERENCES Hospital Facilities experience preferred. Must have knowledge of The Joint Commission, CMS, DFS, OSHA
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. or equivalent doctorate (e.g. Sc.D., M.D., D.V.M.) in medical physics, biomedical engineering, electrical engineering, or computer science. Candidates with non-US degrees may be required to provide proof
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concepts, applications and tools. Collaborate and consult with researchers to analyze problems, recommend technology-based solutions, and design computational strategies for a wide range of biological