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Pediatrics Postdoc Appointment Term: 2 year Appointment Start Date: Open position How to Submit Application Materials: https://forms.gle/xuUxLuwf4cTcBvWs9 (link is external) Does this position pay above the
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
materials research group led by Dr. Mengen Wang is seeking a postdoc researcher to work on computational materials and machine learning-driven materials discovery. The postdoc researcher will perform DFT and
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, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100
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, application components, or other program-related information, visit https://www.orau.gov/doe-fes-postdoc/default.html. All documents must be in English or include an official English translation. Documents sent
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of Singapore). The goal of RESPIRE is to develop Machine Learning (ML) solutions for sleep-related disorders of infants and patients with chronic obstructive pulmonary disease that receive mechanical ventilation
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based on predictions from statistical and machine learning models Postdoctoral scholars are represented by UAW 4121 and are subject to the collective bargaining agreement, unless agreed exclusion criteria
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
to do so. Minimum Education and Experience Requirements Applicants should have (or expect to receive before the start of the position) a PhD in Computer Science or EE/ECE on a topic in machine learning
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at the intersection of scientific computing and machine learning. At a high level, the project is to build neural network models of potentials that appear in Hamiltonians for time-dependent quantum systems. The postdoc
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors
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, currents, water levels, wind, and ice. Machine learning models will be developed to forecast future variations in such dynamic conditions and to incorporate the operational state of the vessel into routing