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Job Description Do you want to help build the digital backbone of the green energy transition, while protecting data security and privacy? We invite you to apply for one of the two fully funded, 3
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the following areas: Knowledge of computer science and machine learning. Familiarity with electrical and electronic engineering. Proficiency in programming languages such as Python, C++, or MATLAB. Experience
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at the intersection of machine learning and operations research to design and operate the water networks of future sustainable societies. Water networks are characterized by their complex topologies and highly non
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(PFAS). You will gain hands-on experience with advanced analytical tools, reactor design, and reaction kinetics, skills that will prepare you for a future career in academia, research, or the water
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Job Description We need to reduce climate impact by replacing fossil fuel. In this PhD project you can help with the green transition by enabling widespread use of alternative fuels. As biofuels and
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to help revolutionizing the future of food safety practice, one that’s safer, smarter, and quicker? We are looking for a highly motivated PhD student to join our dynamic, interdisciplinary research team in
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of the project is to bring about a paradigm shift in the design of switchable materials, by delving into the uncharted territory of f -element valence change (VC). The VC materials will be constructed using rigid
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, visit: www.algoritmer.org . The candidate will conduct teaching as part of the ph.d. programme. You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level
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programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by Kristoffer Almdal and Søren Kramer. We offer DTU is a leading technical university
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, electronics, and neuromorphic computing. You will join an international collaboration between DTU, EPFL, and Max Planck, gaining unique opportunities to work at the intersection of materials science, physics