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Field
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photonic quantum sensing and computing. Experience with control electronics, data acquisition systems, machine learning and AI for control and optimization of experimental apparatus. Experience with vacuum
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geoscientific process models, as demonstrated by presentations, publications and/or repositories Expertise in applying Bayesian statistical methods, machine learning methods, or related statistical inference
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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the
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statistical software & machine learning (e.g., R, Python, SAS, or STATA). Experience working with large population dataset (e.g. EHR, claims data). Background in health informatics, population health research
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
students, and collaborate with AI faculty in vision, robotics, and machine learning across the department. Minimum Education and Experience Requirements Applicants should have, or expect to receive before
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that transforms current AI for Science paradigms focusing on multidisciplinary applications in biomolecular modeling and design, leading to a step-change in Scientific Machine Learning (SciML). They will be
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, pharmacological and chemogenetic experiments in rodents to delineate mechanisms underlying drug abuse. Conduct conditioned place preference, and learning and memory tasks, intracerebral infusions, and
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required
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and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core Responsibilities: Understanding