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for the position. DTU Compute DTU Compute – Department of Mathematics and Computer Science – is an internationally recognised academic environment with over 400 employees and 10 research sections. We broadly cover
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Mechanical, Production, Materials, Industrial or Robotics Engineering, Computer Science, or related discipline, or a similar degree with an equivalent academic level. Approval and Enrolment The scholarship
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interest in pursuing a research career About us: The Dynamical Systems section is part of the Department of Applied Mathematics and Computer Science at the Technical University of Denmark. We strive to be a
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, Computer Science, or related discipline, or a similar degree with an equivalent academic level. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and the candidate
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for security and export control, open-source background checks may be conducted on qualified candidates for the position. DTU Compute DTU Compute – Department of Mathematics and Computer Science – is an
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. Qualifications You should have completed a two-year master's degree (120 ECTS points) in Civil, Architectural, Environmental, Electrical, Mechanical or Industrial Engineering, Autonomous Systems, Computer Science
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Job Description Are you up for the challenge of joining a highly ambitious research group involved in a joint project with international academic and industrial partners towards developing scalable technologies for quantum photonic networks? We are now strengthening our research team on quantum...
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Job Description Are you passionate about robotics, the ocean, and making a real-world impact? Join us in shaping the future of underwater autonomy with a fully funded PhD position focused on cutting-edge motion planning and control for next-generation autonomous underwater vehicles (AUVs). As...
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. You should have a strong academic background in engineering, applied mathematics, or computer science, combined with a clear interest in scientific programming, machine learning, and data analytics
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areas: Knowledge of computer science and operations research Familiarity with renewable energy systems and their challenges Proficiency in programming languages such as Python or Julia Strong problem