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Field
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platform-specific physics knowledge, be it in ultracold neutral atoms, trapped ions or superconducting qubits. This may also involve investigation of the decoherence processes and related question
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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-the-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
, engineering, or a related field is required at the time of appointment. Required Qualifications, Competencies, and Experience A Ph.D. in mathematics, physics, engineering, or a related field is required
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engineering support. Ongoing projects in lab include structural and functional magnetic resonance imaging (MRI) of developing children, and clinical conditions including autism, traumatic brain injury, diabetes
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Post-Doctoral Position - Medical Image Processing - (240000Y9) Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in
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languages such as Python, MATLAB, or C++, and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) preferred. Familiarity with medical imaging processing and reconstruction techniques
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related discipline. Preferred Qualifications Cardiac electrophysiology, Animal handling and surgery (rodents, rabbits, pigs), Donor human hearts, Optical and Electrical mapping, Molecular imaging (western
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schooling behavior of relatively small fish as they navigate complex turbulent flow fields. Using novel analytical techniques for data processing, using numerical models of varying complexity to expand
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with stakeholders. QUALIFICATIONS Doctoral degree in Computer Science, Electrical/Computer Engineering, or a closely related field. Foundation in network security for 5G/6G and O-RAN, including TLS 1.2