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Theory Organizational Behavior Ability and interest to teach in undergraduate and master's programs in English are essential. Applicants need to have completed their PhD (or be very near completion when
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(1.00 FTE), 9-month, fixed-term Assistant Professor (Teaching) position. Reappointment is at the discretion of the Director. The successful candidate will teach upper-division undergraduate courses in
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), 9-month, fixed-term Assistant Professor (Teaching) position. Reappointment is at the discretion of the Director. The successful candidate will teach upper-division undergraduate courses in Spanish and
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skills (Python) and knowledge of deep-learning frameworks (PyTorch) are expected. A certain affinity towards turning complex concepts into real-world practice is desired. The successful candidate is
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(e.g. deep learning, language models and responsible AI). Minimum Qualifications PhD or other doctoral degree in biostatistics, statistics or strongly related field. Record of high-quality scientific
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Desirable: B1 A specialism in HR analytics or deep learning. Skills Essential: C1 Ability to communicate material of a specialist or highly technical nature and to be effective both orally and in writing at a
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science, and educators to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater understanding to the world. For more
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the requisite experience. Desirable: B1 An awarded (or recently submitted or near completion) PhD in subject specialism or equivalent. B2 Experience with high dimensional statistical, machine learning and deep
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model we deploy and support the ecosystem with training, advisory, and AI infrastructure. CeADAR is seeking a data scientist with solid experience in machine and deep learning research and development
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
of the trajectory. This grant targets the development and rigorous benchmarking of novel, energy-efficient CAD-based deep learning architectures that fuse visual and inertial modalities for the robust 6D pose