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the possibility of yearly renewal subject to funding availability. Key Responsibilities • Conduct and lead research in 3D computer vision, deep learning, and AI for digital twin generation, publish findings in top
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funding availability. Responsibilities • Design and implement deep learning architectures, AI agent pipelines, and computer vision algorithms to achieve project goals (33%) • Conduct full stack development
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acquisition and management. This role directly builds upon Ph.D. research by applying advanced 3D imaging, algorithm design, machine learning, software engineering and visualization techniques to a real-world
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strong interest in machine learning and deep learning algorithms · Research and publication experience in health outcomes research Application Materials: · CV · Cover letter · Contact information for three
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qualified candidates to apply for a postdoctoral research position. The research will focus on statistical modeling, machine learning and trustworthy AI to develop effective and efficient algorithms
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support the CPP research, grant applications, and outreach. During the academic year the fellow will teach one or two courses. Position Qualifications: Required: PhD in Public Policy, Political Science
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members across electrical engineering, earth science, signal processing, and machine learning to ensure methodological rigor and practical relevance. Qualifications: -Ph.D. in Electrical Engineering
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interest • Report scientific results in peer-reviewed academic journals and talks. Required Knowledge, Skills, and Abilities: • PhD. in Physics, Chemistry, Material Science, Photonics or related field
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based on personal preference in consultation with the supervising faculty. Preferred Qualifications: PhD degree in a relevant field of sciences or engineering. Strong communication skills (written/verbal
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experiences related to one or more of the following areas: embedded or mobile device security, embedded systems applications, machine learning security, user-centric security and privacy. 3. Experience and