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hardware Experience with atomic layer deposition and process development Experience with thin film and materials characterization Strong background in computational materials science and machine learning
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 hour ago
the development and implementation of machine learning models Special Physical/Mental Requirements Special Instructions For information on UNC Postdoctoral Benefits and Services click here Quick Link https
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• Trainees (postdocs and students): 45 • Research spans eight hubs—Statistical Learning & Data Science; Genomics & Genetics; Imaging; Mobile & Wearable Data Science; Epidemiology; Health Policy; Medical
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. The project takes an explicit social science approach and aims to use Machine Learning and Social Network Analysis methodology to 1. analyze the current and developing opinions of new clean energy technology
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, particularly radionuclides, on a continental scale. The aim is to develop a new class of inverse Bayesian models, STE-EU-SCALE, combining innovative forward dispersion models, machine learning techniques, and
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02215, United States of America [map ] Subject Areas: Computer Science / Artificial Intelligence , Data Science , Machine Learning , Software Engineering Data Science / Artificial Intelligence , Data
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infrastructure, with the state-of-the-art reinforcement learning and generative AI, to detect, prevent, and preemptively mitigate intelligent attacker vectors. Supportive Mentoring: The postdoc will be guided by
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Experience in machine learning Knowledge of SDN and NFV Knowledge of basic TCP/IP protocols What you will do Conduct high-impact research and publish in leading journals and conferences Shape research
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, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology. Achieving
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(e.g. R or Python), statistics, machine learning, and data science. A good publication record with respect to your career stage and research interests in climate impacts in mountain regions complete your