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complementary and synergic methods at the intersection of Artificial intelligence, Machine learning, Numerical simulation, Formal verification. Such methods include, among the others: AI-guided simulation
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, and the military. Both quantitative and qualitative approaches would be relevant, and comparative approaches (cross-sector, cross-institutional, cross-national, or other) are welcome, but not required
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economic assessments machine learning or proxy-model based methods field scale simulation geological features geomechanics reactive flow The PhD fellow are not expected to master all these topics. Project
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. In addition, you must have: a solid foundation in energy technology and a strong understanding of artificial intelligence (AI), machine learning (ML), and data-driven modeling documented experience
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Sociology » Sociology of labour Sociology » Sociology of religion Sociology » Urban sociology Sociology » Other Educational sciences » Education Educational sciences » Learning studies Educational sciences
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, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. In order to support machine learning, the project will make use of historical radar
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required to teach part of a course in fundamental fluid mechanics, taking joint responsibility for lectures, exercise sessions, and the examination. Your immediate leader will be James Dawson. Duties
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Teach and supervise students at bachelor’s, master’s, and Ph.D. levels Further develop existing courses or create new courses and learning methods within interaction design, human-computer interaction
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of Singapore). The goal of RESPIRE is to develop Machine Learning (ML) solutions for sleep-related disorders of infants and patients with chronic obstructive pulmonary disease that receive mechanical ventilation
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Fellow will acquire. Access to career guidance will be provided throughout the doctoral education. The University of Stavanger funds the position. It is connected to the international research project