59 phd-in-software-engineering-positions "https:" Postdoctoral research jobs in United States
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research facilities, and high-performance computing resources. Education Requirement: - MBBS, MBBCh, MS, MD, PhD, or MD/PhD in Radiology, Medical Physics, Biomedical Engineering, Computer Science, or a
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the terms of their appointment. Qualifications include a PhD degree or equivalent in biostatistics, statistics or related quantitative field with considerable knowledge and experience using the R software
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just 75 minutes southeast of Columbus, Ohio. Minimum Qualifications: PhD in Physics, Nuclear Engineering, Nuclear Chemistry, or related fields Preferred Qualifications: Knowledge in accelerator-based
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until the position is filled. To be considered, all applicants must submit a cover letter, curriculum vitae with a full publication list, transcripts of Master’s and PhD degrees, research statement, and
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equipment (copy machine, fax machine, multi-line phone). Applications are being accepted on line at https://unmc.peopleadmin.com/postings/97497 Inquiries: David Warren, PhD at david.warren@unmc.edu Required
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experience using statistical software (e.g., R and Python) and AI tools (e.g., Claude Code) are a key requirement for the position. Successful candidates should show potential to excel in tasks related to meta
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UnitedKingdomTime) Position Description: Apply Position Description About Sandia: Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation, with
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Number req25611 Department Space 4 Center Department Website Link https://s4.arizona.edu/ Location Tucson Campus Address Tucson, AZ USA Position Highlights The Space4 Center at the University of Arizona
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, including calibrating hardware and software infrastructure for research, sensor data collection and analysis; validating and disseminating research protocols and tools; creating technology prototypes and
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#:39540 Job Summary: How can we turn the vast and rapidly growing collections of publicly available biological data into reusable engines for discovery? And how do we build the software infrastructure