149 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Technical University of Denmark
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Documentation of experimental procedures, results, and technical learnings Preparation and delivery of clear, well-structured presentations of plans, methods, and results to internal teams and external
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responsibility for leading highly skilled technical staff Fluency in English - both verbal and written, preferably also Danish but at least an interest and ambition to learn Danish Furthermore, it is desirable
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focus is both to acquire greater knowledge about basic scientific problems and to conduct research oriented towards use in societies and companies. Technology for people DTU develops technology for people
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development. You are able to learn self-motivated and independently and pursue new knowledge as needed. Openness and collaborative skills (e.g. humility & will to compromise). Effort-dedication to documenting
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modelling, autonomous materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from BSc, MSc, PhD to lifelong learning
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willingness to learn Your Skills and Attributes We hope you can tick off some of these: A structured approach to tasks The ability to juggle multiple tasks with ease A desire to contribute to the green
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robotic systems (e.g., ABB, KUKA, or UR). You have practical experience with machine development, material testing, mechanical characterization, or process parameter optimization. Furthermore, it is an
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and daily operation of DALSA Coordinate and host scientific workshops at DALSA Develop and teach at automation courses offered by DALSA Our expectations of you A PhD in a field relevant to automation in
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are applying for the position. If you wish further information about the position, please contact Simon Ringive at simri@dtu.dk or Phillip Yttung at phiyt @ dtu.dk to learn more. Applications
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industry-facing research collaboration and coordinate cross-partner workflows in planning, data-sharing, and iterative decision-making across industrial and academic stakeholders. Teach and supervise PhD