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Learning has an open position for a doctoral student with a background and strong interest in deep generative learning and computer vision/remote sensing. The successful candidate will join a project funded
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-edge machine learning methods with empirical insights from the educational arm of the project. A central technical challenge guides this position: How can an LLM-based AI social agent be designed, fine
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Faculty.Instructor.Adjunct Electrical and Computer Engineering - Pennsylvania-Pittsburgh - (26005016) Qualifications: Ph.D. in Electrical Engineering with expertise in electrical power systems ECE
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Faculty.Instructor.Adjunct Electrical and Computer Engineering - Pennsylvania-Pittsburgh - (26005055) Qualifications: Ph.D. in Electrical Engineering with expertise in electrical power systems ECE
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 2 months ago
substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required
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Qualifications PhD in Electrical Engineering, Computer Engineering, Computational Science, Computational Engineering, Aerospace Engineering, Computer Science, Math, Physics, or related discipline. Experience
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even makes room for good conversations over high-quality tea. Job description As a PhD candidate, you will contribute to cutting-edge research on next-generation wireless communication and sensing
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learning, machine learning, AI, and specialized computer vision courses, as well as support curriculum development, academic leadership, and mentoring within the department. You will supervise PhD candidates
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substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required
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deadlines. Experience Essential: E1. Research experience aligned to the goals of at least one of the Centre for Data Science and AI’s programmes with commensurate output. E2. Experience in machine learning