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computational cultures, and the methodologies and theories, of statistics, logic, language technology, ethics and machine learning, in new and unique ways. The focus of Integreat is to develop ground-breaking
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computational cultures, and the methodologies and theories, of statistics, logic, language technology, ethics and machine learning, in new and unique ways. The focus of Integreat is to develop ground-breaking
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» Control engineering Computer science » Cybernetics Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Apr 2026 - 23:59 (Europe
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of the Software Engineering unit . About the project This PhD fellowship is part of the national AI Centre for the Empowerment of Human Learning (AI LEARN). AI LEARN is a new Centre dedicated to the empowerment
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at the intersection of deep learning and computer systems. The successful candidate will join an international and collaborative research environment and contribute to advancing efficient AI systems through close
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fellowship is part of the newly established AI Centre for the Empowerment of Human Learning (AI LEARN) . Your immediate leader will be the leader of the Software Engineering unit . About the project This PhD
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learning optimization at the Department of Computer Science, Norwegian University of Science and Technology (NTNU). The position is supported by the EU Horizon project CIRES and offers the opportunity
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, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier. Duties of the position Fundamental contributions in
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selection criteria Experience with AI / probabilistic AI / Machine Learning / Reinforcement Learning Experience with numerical optimization and MPC Strong programming skills (Python, C) Personal
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Experience with AI / probabilistic AI / Machine Learning Experience with numerical optimization and MPC Strong programming skills (Python, C) Experience with predictive maintenance, fatigue, fault detection