44 structures "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" PhD positions at NTNU Norwegian University of Science and Technology
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-funding from industry and academic partners. You can read more about NICE on https://www.ntnu.edu/nice. Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research
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well as researchers from 15 international institutions. More on the project at http://sure-ai.no . Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality
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), it is important that you are able to: Have a high level of personal responsibility, initiative, motivation and ability to work in a project team as well as independently. Work in a structured way, set
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structured way, set goals and make plans to achieve them Present and discuss your research with other professionals Be highly motivated by fundamental scientific research of practical relevance Get involved
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team Work in a structured way, set goals and make plans to achieve them Present and discuss your research with other professionals Get involved and contribute constructively with feedback Show enthusiasm
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arising from the inclusion of scrap, and to control the processing parameters such that the structural integrity of the cast components can meet with the demands to performance. The starting date is August
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characteristics Highly motivated for applied and collaborative research. Excellent communication and teamwork skills. Self-driven, structured, and reliable. Innovative mindset and ability to work across disciplines
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of the position Numerical simulations of nonlinear photonic waveguides and devices Photonic design of hybrid integrated laser structures for manufacturing at NTNU or in collaboration with external foundries
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transactions; Ship design and construction; Voyage planning and optimization; Condition monitoring and maintenance; Crew training; Maritime traffic and ship surveillance; Decarbonization and energy management
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, and reinforcement learning for adaptive decision-making. A key aim is to connect wireless phenomena to learning robustness by combining physical-layer signal structure and signal-processing insights