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collaborates with leading tech firms and advance research in robotics, AI, battery technology, aerospace, water systems and sustainable energy. Learn more at unr.edu/engineering Exempt Yes Full-Time Equivalent
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, battery technology, aerospace, water systems and sustainable energy. Learn more at unr.edu/engineering Exempt Yes Full-Time Equivalent 100.0% Required Attachment(s) Please note, once you submit your
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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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strategies within it. You will combine archaeological and landscape data (maps, satellite imagery, archaeological datasets) with machine learning approaches to build a system that highlights promising
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improve high-throughput experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and
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backgrounds in adjacent areas and a firm commitment to learning glycobiology approaches are also encouraged to apply. Interested candidates should include a CV, brief statement of research interests, and
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for Transportation (VITA ) is looking for a postdoctoral researcher in the area of Generative AI. VITA research interests lie at the intersection of Computer Vision, Machine Learning (Deep Learning), and Human-Robot
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project TARGETWISE. The candidate will be responsible for conducting machine learning omics data analysis within the computational team. The details on responsibilities, obligations and rights
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intelligence and machine learning across several domains of physics and astronomy. The successful candidates will develop an integrated image-processing pipeline and apply it to three distinct problems: rare
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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