779 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions in United States
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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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science, energy, national security, and health. Our researchers develop scalable machine-learning models, deep-learning architectures, and data-driven methods for platforms ranging from edge sensors and
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, learning, well-being, social experiences, and decision-making. HARP is developing a longitudinal multimodal research resource to study human-AI interaction and its impacts using student-informed, privacy
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shoulders up to 25 pounds. Standing and sitting at computer terminals and laboratory bench completing repetitive tasks for extensive periods of time. Continuous working with materials requiring personal
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learning and benthic systems. This position offers an opportunity to contribute to cutting-edge research, particularly advancing the use of remote sensing datasets and machine learning for constructing
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. • Expertise in metabolomics with mass spectrometry is desired. • Strong general computer skills, experience with databases and scientific applications, and ability to quickly learn and master various computer
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established skills and a strong aptitude to learn new skills. Communication · Fluent in English (reading, writing, and speaking). · Proficient in giving scientific presentations, with demonstrated experience
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: Ph.D. in Robotics, Mechatronics, Electrical Engineering, or a closely related field (for example, mechanical, computer, or controls engineering), conferred by the start date Demonstrated experience
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, measurement, and evaluation strategy, with a focus on cross-sector data infrastructure, linkage, performance measurement, evaluation, and continuous learning. Responsibilities: 1. Serve as a scientific partner
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at the intersection of AI and any humanities or social science discipline. Fellows will have the option to teach one undergraduate course each year. The first year of appointment will run 1 August 2027–31 July 2028