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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 13 hours ago
as one of the nation’s top public universities . Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work
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astrophysics (completed by the start date), demonstrated experience in large-scale structure simulations, working knowledge of applications of machine learning techniques in cosmology and/or astrophysics (in
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and advanced attendees Schedule Flexibility with work schedule Compensation Grade LOA https://www.unr.edu/hr/compensation-evaluation/salary-schedules/loa-and-postdoc Exempt Yes Full-Time Equivalent 0.0
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research staff, PhD students, or postdocs Providing guidance, training, and technical support to others in the research team Ensuring compliance with research ethics, safety regulations, and institutional
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, software and data engineering, data mining, machine learning, and Artificial Intelligence. Qualified candidates are invited to submit their applications through the web portal available at https
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data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods
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excellence and values innovation, collaboration, and life-long learning. To foster the talents and aspirations of our staff, Stanford offers career development programs, competitive pay that reflects market
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statistical and machine learning methodologies to analyze and predict aspects of the collected data With the guidance of Drs. Stuber and Bruchas, develop experimental methodologies related to two-photon imaging
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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assimilation, machine learning, and optimization techniques. Experience in student mentoring. Publications in leading journals within the field. Preferred Qualifications PhD in Environmental Modeling. More than