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Field
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health To be eligible, candidates must: Have received a PhD in computer science, information science, bioinformatics, biostatistics, mathematics, nutrition, epidemiology, biomedical engineering, medicine
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on an optical table and integrating novel optics to microscopy are a requirement for this position. Knowledge in computational imaging, mathematical modeling, strong computer programming skills in MATLAB and/or
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related field; experience with fMRI experimental design and analysis is not required but highly desired; a strong mathematical/programming skill is highly desired; and a track record of research
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 04-Jun-25 Location: Princeton, New Jersey Type: Full-time Categories: Other Staff/Administrative Internal Number: 272540364 Position: Postdoctoral Research Associate Description: The condensed matter spectroscopy...
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, statistics, applied mathematics, bioinformatics, computer science or a related field and 2) completed postdoctoral training prior. To be considered, those interested must apply through The University
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a Ph.D. in computer science, engineering, mathematics, or other related fields. Successful candidates must have Ph.D. or terminal degree prior to beginning employment at Penn State. This appointment
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 16 hours ago
/computer science and information systems, computer science/computer science and information systems, and B.S. in mathematics/M.S. in mathematics. To implement its academic programs, the college provides instruction
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Geography / College of Letters & Science - Mathematical, Life, and Physical Sciences / UC Santa Barbara Position overview Position title: Postdoctoral Scholar with Center for Spatial Studies Salary range
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record of peer-reviewed publications. A background is required in computer programming (including Julia and/or C/C++), applied mathematics and statistics. Please upload your application materials via
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Measure Theory : Leveraging foundational mathematical frameworks to design robust modeling approaches. 2) Deep Learning : Exploring cutting-edge techniques such as multimodal data integration, diffusion