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Field
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world and a suite of associated machine learning tools. The incumbent will be advised by Dr. Laurel Symes (CAPS, [email protected]). Depending on the research direction, collaboration and additional
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stimulation (TMS), and transcranial direct current stimulation (tDCS) through interdisciplinary collaborations. Behavioral measurements and physiological recordings, including facilities for computer-based
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 3 months ago
/Administrative Internal Number: 25848 POSTDOCTORAL ASSOCIATE, Jameel Clinic for Machine Learning in Health, seeks to support a collaborative research program between the laboratories of Professor Omer Yilmaz, Koch
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of the future Center and Protect OHIO, translating research findings into outreach-appropriate sessions, building active-learning sessions for stakeholders, learning best practices for educating and engaging
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
Posting Description POSTDOCTORAL ASSOCIATE, Jameel Clinic for Machine Learning in Health, seeks to support a collaborative research program between the laboratories of Professor Ömer Yilmaz, Koch
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sensors, RGB/IR cameras, video systems, insect traps, and other devices to build predictive, AI- and machine-learning based models for monitoring grain quality and detecting deterioration due to mold
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. Knowledge of survival analysis. Knowledge of machine learning methods. Other Requirements Application materials must include: Curriculum Vitae (CV) Statement of research interests Names of three professional
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are essential. In addition to applicants’ prior accomplishments, we would like to learn what motivates them, how they approach unfamiliar problems, and what they hope to contribute to, and learn from
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 20 days ago
); and propagation of physics-traceable soil moisture uncertainty into precipitation estimates. Machine learning approaches are welcome as tools within this framework — for example, learning the space–time