1,050 data-"https:"-"https:"-"https:"-"https:"-"University-of-Aberdeen" Postdoctoral positions in United States
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Field
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving
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- to ensure that data is comparable and integrated across organisms. How to Apply Please send your complete application to Dr. Adrienne Roeder at ahr75@cornell.edu . The application should include: A cover
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and expertise 4. Names and contact information for 3 references The priority deadline is April 17, 2026, but all applications will be considered until the position is filled. Questions about the
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the
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System Administration . Position Summary: University Information Services (UIS) provides technical services and enterprise applications to the University of Colorado’s (CU) four campuses and the Office of
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 months ago
-on research experience in the preparation and deployment of the EXCITE payload, with topic areas including: infrared detectors and readout, cryogenics and cryocoolers, optics, data acquisition, balloon attitude
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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post Doctoral Scholar - Surgery Department
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-system data, simulation platforms, and digital-twin or real-time environments as appropriate. Collaborate with researchers across power systems, controls, cybersecurity, and AI/ML to develop publications
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Position Details Position Information Announcement Number STAFF - VA - 26260 For questions regarding this position, please contact: Molly Patten Business Office Manager molly.patten@montana.edu
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in pediatric or related health sciences fields. Scientific Knowledge: Strong understanding of research design, statistical analysis, and data interpretation methods relevant to pediatric research