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field. Experience: At least three years of strong record of research productivity in machine learning and artificial intelligence. Expertise in AI/ML and interests in business and policy applications
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-energy impact events using LS-DYNA and other applicable numerical analysis methods/computer simulation codes. Prepare and submit proposals/budgets to acquire new funding. Meet with prospective clients
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cybersecurity research. Who you are: You have BS in machine learning, cybersecurity, statistics, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years
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of the four campuses (two in Chicago, one in London, and one in Hong Kong) reflects the architectural traditions of its environs while offering a state-of-the-art learning environment. Chicago Booth is proud
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, towards future colliders. Cutting-edge machine learning developments for classical and quantum computational platforms are pursued in the group to benefit particle physics and beyond. Experience Candidates
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, United States of America [map ] Subject Area: Computational harmonic analysis and machine learning Appl Deadline: none (posted 2024/10/14) Position Description: Apply Today is the last day you can apply for this position
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validating deep learning models for the prediction of disease progression from ophthalmic data. Skills include working with image or computer vision-based toolkits, development of multimodal, multidata type
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control under high inverter-based resources (IBRs). • Develop and apply artificial intelligence (AI)/machine learning (ML) techniques for power system planning, operation, control, and cybersecurity
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encourages all students, faculty and staff to support a diverse and inclusive university in which to work, study, teach, research and serve. No person shall be denied employment on the basis of any legally
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, study, teach, research and serve. No person shall be denied employment on the basis of any legally protected status or subjected to prohibited discrimination involving, but not limited to, such factors as