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Field
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neuroethology and robotics. This position focuses primarily on the neuroethology aspects of our research program, with particular emphasis on understanding the behavioral and neural mechanisms underlying active
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applications for recording, analyzing, and reporting findings Strong organizational and documentation skills Ability to build and maintain effective working relationships with faculty, staff, and students
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performs MRI research and development of advanced multiparametric methods for the evaluation of primary and metastatic brain tumors. Recent work incorporates machine learning methods to advance
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. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and deep learning techniques to improve image processing and trait prediction. Analyze large
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together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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-looking vision for a 21st-century education, and a deep commitment to promoting inclusion, we open a world of opportunity to students and empower them to make a difference around the world. Through learning
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About the Opportunity This job seeks a postdoc to work on one or more projects related to the development and assessment of wearable robotics. Possible projects topics include: Developing machine
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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(s). Knowledge of pulse generators, oscilloscopes, multimeters, power supplies, diode lasers, telescopes, cameras, range finders, lathes, milling machines, 3D printers, band saws. Salary: Compensation
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machine learning, computer vision, human-computer interaction, or similar relevant areas. Experience in research or development on bias, interpretability, and/or privacy in machine learning/AI is necessary