28 distributed-algorithm-"Prof" PhD positions at Technical University of Denmark in Denmark
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Job Description The aim of this PhD project is to investigate the immediate and long-term deformation behaviour of plain and fiber-reinforced concrete using distributed fibre-optical sensing (FOS
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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly
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our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by Prof. Henning
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. Further information Further information may be obtained from Asst. Prof Charalampos Orfanidis or Prof. Xenofon Fafoutis . You can read more here about working in our section, at DTU and in Denmark. If you
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. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by Prof
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. You will work under the supervision of Prof. Francisco C. Pereira, Assoc. Prof. Carlos Lima Azevedo (DTU), Dr. Biagio Ciuffo and Dr. Georgios Fontaras (JRC). You will work on research focused
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photonics’, led by Assoc. Prof. Thomas Christensen, who moved from MIT to DTU in 2023. Funded by a Villum Young Investigator program (link ), the project aims to uncover novel kinds of photonic topology using
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programme, please see DTU's rules for the PhD education . Assessment The assessment of the applicants will be made by prof. Patrizio Mariani, Dr. Jon Christian Svendsen and Dr. Fletcher Thompson We offer DTU
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academia and industry. You will be involved in the “DTU Alliance” project in collaboration with Prof. Anna Scaglione at Cornell University, with the opportunity to undertake a research stay of 5–9 months
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing