616 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"SUNY" Postdoctoral positions in United States
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applied for without regard to race, color, religion, sex, age, national origin, disability, marital status, sexual orientation, military/veteran status, gender identity, or other non-merit factors. We
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on developing machine-learning surrogates for electronic structure and electrostatic potential and using these models to predict structural and electronic evolution under applied bias. Methods may include density
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science, including electronic structure methods molecular dynamics, and scientific machine learning. Experience with High-Performance Computing (HPC) systems and intelligent workflows. Demonstrated
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The Center for Advanced Study of Teaching and Learning (CASTL) is seeking applications for a qualified postdoctoral research associate to work under the mentorship of Dr. Julie Cohen on several
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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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disseminate research results and data in peer-reviewed publications as well as presentations at international conferences. Required Qualifications: Education/Training- PhD in Electrical and Computer Engineering
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The Opportunity: Conduct research in Natural Language Processing (NLP), Computer Vision, and Artificial Intelligence (AI), with the goal of publishing in top-tier conferences such as CVPR, ICCV
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status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that is best when
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tolerance for varietal selection. Learning Objectives: Participant will gain laboratory, field, and programming skills to develop the digital twin and other AI models using ground and above-ground sensors and
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machine learning models to integrate real-time monitoring data. Collaborate with colleagues in computer science and computer engineering to develop models. Contribute to the dissemination of research