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Posting Details Student Title Classification Information Quick Link https://chapman.peopleadmin.com/postings/40251 Job Number SE212124 Position Information Department or Unit Name Fowler School of
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Mathjobs.org | 22 days ago
families of algorithms for cryo-electron microscopy (cryo-EM) and broader applications in data science * Protein structure prediction: Combining traditional and machine learning approaches to protein
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families of algorithms for cryo-electron microscopy (cryo-EM) and broader applications in data science * Protein structure prediction: Combining traditional and machine learning approaches to protein
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CFM-Centro de Física de Materiales/MPC-Materials Physics Center | Donostia-San Sebastian, Pais Vasco | Spain | about 2 months ago
to establish a closed-loop platform that combines computational inverse design, robotic synthesis, online characterization, and machine learning-driven optimization of plasmonic nanoparticles. Join us
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: https://www.nist.gov/people/peter-bajcsy Keywords imaging; image analyses; machine learning; software engineering Eligibility citizenship Open to U.S. citizens level Open to Postdoctoral applicants
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real-world problems. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading
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approaches with regard to teaching. High-quality research relating to AI and/or machine learning in Economics TO APPLY: https://www.tamucc.edu/human-resources/careers/index.php All required documentation
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approaches with regard to teaching. High-quality research relating to AI and/or machine learning in Economics TO APPLY: https://www.tamucc.edu/human-resources/careers/index.php All required documentation
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
translation of neuroengineering innovations into improved human health. Within this cluster, the DSS position will provide leadership in machine learning, statistical, and AI frameworks that transform
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Mapping Site (UMS), a unique test environment for utility mapping technologies. Current machine learning models and their training data are limited in size, comprehensiveness, and realism – resulting in