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focuses on translational research at the intersection of bioelectronics, healthcare-focused nanofabrication, and emerging applications of machine learning in radiology. Our team operates within a state-of
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to this position contact Eric Markvicka eric.markvicka@unl.edu Job Category Job Category (old) Post Docs & Other Academic Job Type Full-Time Temporary Position funded by grant or other form of temporary funding? Yes
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Title Post-Doc Research Associate Vacancy ID PDS004549 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC Position Location North Carolina, US Hiring Range
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
Title Post-Doc Research Associate Vacancy ID PDS004549 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC Position Location North Carolina, US Hiring Range
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. The concept has lately gained increasing interest from researchers in applied mathematics and machine learning. This is due to its remarkable flexibility, mathematical elegance, and as it has produced state
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Description Department of Veterinary and Animal Sciences Faculty of Health and Medical Sciences University of Copenhagen We seek to appoint a highly motivated and dynamic post doc with interest in neonatology
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, Computing and Computational Sciences Directorate, at Oak Ridge National Laboratory (ORNL). This position presents a unique opportunity to develop cutting-edge high-performance computing (HPC) and machine
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 hours ago
Position Title Post-Doc Research Associate Vacancy ID PDS004582 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC Position Location North Carolina, US Hiring Range
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: · Payroll & Benefits Orientation for Post-Doctoral Fellows | University of Colorado (cu.edu) · benefits guide cover-post-doc-2024 (cu.edu) Qualifications: Minimum Qualifications: Applicants must meet
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for the development and implementation of innovative statistical and machine learning approaches for analysis of genetics and genomics data. We are particularly interested in applicants who have experience with methods