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behaviour. This will include developing and using state-of-the-art image recognition algorithms to create digital twin models as well as statistical and machine learning methods for analysing large-scale
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that merge thermo-fluid dynamic laws, deep learning, and experimental data. A central goal is to overcome current limitations in TES operation and optimization, enabling discovery of new high-performance and
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have regular activities in Greenland. Learn more on aqua.dtu.dk . The Section for Oceans and Arctic in DTU Aqua covers a wide research spectrum from oceanography, population ecology, observation
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Job Description You will join a supportive and dynamic research team working at the intersection of machine learning and operations research. Your main task will be to design and implement ML
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, biochemistry, molecular biology, biotechnology, or a related discipline. You must have: Expertise in either computational protein design or wet lab techniques, with a willingness to learn the complementary skill
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schemes. Building ion trapping setup for Ca+ ions. Learning/operating fabrication and characterization equipment e.g. STM. Simulating fabrication methods. Collaboration with other groups at NQCP and
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undermine this future. Can you see how Machine Learning, Computer Vision, and Robotics can open up opportunities for autonomously operating agricultural robots? Are you passionate about making agriculture
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with society. Whether our contributions come in the form of excellent research, innovative solutions, education or learning, we must make a positive difference to society and contribute to a sustainable
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consumers. You'll gain deep interdisciplinary experience—combining multiple data layers and approaches including bioinformatics, machine learning, food safety management, regulatory science, genomics and user
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some background in one or more of the following areas: Mathematical Optimization / Operations Research Reinforcement Learning, Machine Learning, and/or Multi-agent systems Game Theory Algorithms