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services through collaborative research and knowledge exchange. Developing and leading research projects and research groups. Enhancing the department’s international networks and collaborative initiatives
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on constrained platforms using techniques such as model compression, quantization, and hardware-aware neural network design. Investigating mechanisms that protect the integrity and reliability of deployed AI
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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, encouraging creativity, diversity, empathy, and teamwork. You will have a great opportunity to build strong networks with internationally known researchers at DTU and other universities as well as industrial
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research activities, and you like to explore research collaborations with colleagues inside and outside your network. You must be responsible for the teaching of courses. DTU employs two working languages
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safer, more reliable, and more sustainable renewable energy systems. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods
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, predictive modelling, and autonomous maintenance solutions. You thrive on scientific discovery, enjoy tackling complex multi-physics problems, and have the drive to explore innovative concepts
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history, list of publications (applicants applying for the position as associate professor should indicate scientific highlights), H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including
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green transition. Due to the complexity and heterogeneity of the biological mechanisms underlying fermentation, achieving optimal performance often requires fine-grained, time-dependent, control
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population data will be considered a strong advantage. The ideal candidate is comfortable learning new analytical methods and working with large and complex datasets. Qualification requirements PhD stipends