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including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions. Unlock your potential with tuition benefits , take
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and technical reports, as well as seminar and conference presentations Active participation in professional organizations Basic Qualifications: A PhD in Mathematics, Applied Mathematics, Computational
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. Required Education Appropriate doctoral degree Preferred Qualifications PhD in Neuroscience Prior experience with electrophysiology and/or two-photon microscopy imaging Data analytical skills including
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Mississippi. Apply computer vision and machine learning approaches to integrate ground-based imagery, remote sensing data, and lidar data for high-resolution flood detection and mapping. Develop and calibrate
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organizing talks, attending workshops, and contributing to collaborative projects that explore the intersection of complex systems and public health. Qualifications PhD in a related discipline (e.g
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the computer science research conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed proceedings
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computational approaches. Ongoing projects include: 1) characterizing heavy substance use with precision functional mapping; 2) studying the association of substance use/exposure with longitudinal brain
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
for computational equipment and travel. Minimum Education and Experience Requirements PhD in Physics, Astronomy, or related field Required Qualifications, Competencies, and Experience Experience in any of the above
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-generation computing, including quantum emitters and neuromorphic transistors. The ideal candidate should have a strong background in solid-state physics, electronic materials, or device fabrication and
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on semiconductor devices for next-generation computing, including quantum emitters and neuromorphic transistors. The ideal candidate should have a strong background in solid-state physics, electronic materials