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structural design, 3D printing robots, sensors, safe and efficient human machine interfaces, processing units, and software components into a cyber physical construction system. The result would be
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Empirical Software Engineering Mining of Software Repositories and Issue Tracking Systems Fluency in English is required. For further information, please contact Professor Fabrizio Montesi (fmontesi
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spanning a wide range of fields including applied cyber-physical systems, advanced mechanical systems, modelling and mechatronic prototyping. Your profile To complement our team, we are looking for one
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-making as an “asylum lottery”. As AI-supported decision-making becomes embedded in such systems, there is a concern that inherent bias in data will be replicated. To study and mitigate these effects, a new
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. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. You can read more about career paths at DTU here . Further information Further information may be obtained from
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
the potential of biological systems. Big data approaches and analysis of biological systems are key research instruments at the Center. DTU Biosustain utilizes these advances for microbial cell factory design to
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student compared to other students the year you graduated ("ranks as no. 6 out of 111" or "ranks as among the best 8 percent") or if that is not possible, general information from your University as to how
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strong in collaboration? Do you see it as a unique opportunity to spend 9 months of the PhD in China? If yes, we look forward to reading your application to our PhD Stipend. At the Faculty of Engineering
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universities, and three research and technology organizations. This PhD project is focused on glass cutting, where large, laminated glass panels are cut to sizes for window production. The process involves pre
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recent large-scale capabilities in physics. Reliability, exploring uncertainty quantification and robust inference in machine learning. Explainability, leveraging identifiability and unique recovery