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neuroscience. The position is open under specific projects as well as general research involving the application of methods from theoretical physics, mathematics, and machine learning with the goal to understand
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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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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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on intelligent observing systems using machine learning and data assimilation methods in the ACTIVATE project. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/289326
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours 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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subsea digital twin of deep-water mooring lines for floating offshore wind turbines. The digital twin will be integrated with machine learning algorithms for detection of primary entanglement due
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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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(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
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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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comparable qualification) in a relevant discipline (computer science, mathematics, AI) Expertise in one or multiple of the following areas: Deep Learning, Computer Vision, Signal Processing (Synthetic Aperture