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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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) or Machine Learning models. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness of the assessment. All components assembled
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(e.g., Kalman Filter) or Machine Learning models. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness
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equal gender distribution. We are located in Lyngby, Hirtshals, Nykøbing Mors, and Silkeborg and have regular activities in Greenland. Learn more at aqua.dtu.dk Technology for people DTU develops
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machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
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activities, i.e., teaching and supervision of BSc and MSc student projects at DTU. We are looking for candidates with Strong skills in AI, Machine Learning, and/or Data Science, preferably with experience in
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into this environment are invited to apply. Experience in quantum nanophotonics, quantum photonic devices, nanoscience, nanotechnology, and quantum dots is welcomed. Learn more about the project here: nikaakopian.org
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European level Participation in teaching activities Teaching and Learning education You must contribute to the teaching of courses. DTU employs two working languages: Danish and English. You are expected
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Job Description Are you passionate about renewable energy and eager to apply machine learning to real-world challenges? Join our research team at DTU and work on groundbreaking advancements in
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have been responsible for You can learn more about the recruitment process here . Applications received after the deadline will not be considered. All interested candidates irrespective of age, gender