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Job Description DTU, Department of Civil and Mechanical Engineering, the Section for Manufacturing Engineering invites applications for a PhD position (3 years) on the topic of simulation of process
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Job Description The Institute of Mechanical and Electrical Engineering at SDU invites applications for a PhD position in Neuromorphic Brain-Computer Interface Design. Are you a multidisciplinary
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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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to contribute to a collaborative, interdisciplinary research environment Are eager to learn and explore new ideas at the intersection of ML and optimization Can program efficiently in one or more languages
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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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enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . We offer DTU is a leading technical university globally recognized for the excellence
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for the efficient formation of high-value compounds. Advanced NMR methods and computational data analysis will be compounded to devise novel reactions towards pharmaceutical precursors, polymer building blocks and
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qualifications As our new colleague in our research team your job will be to develop novel computational frameworks for machine learning. In particular, you will push the boundaries of Scalability, drawing upon
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, including electrical engineering, control theory, industrial engineering, electronics engineering, energy policy, data science, and applied mathematics. As part of the Alliance program, your project will be
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Job Description The Department of Civil and Mechanical Engineering of the Technical University of Denmark (DTU) has an open PhD position on the topic of “Automation of tool wear measurement and data