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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
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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of
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research funding" at the PhD Programme in Management. The position is available from 1 September 2025 (or as soon as possible thereafter). The research project The PhD position will focus on the assessment
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international PhD researchers, gaining access to dedicated training events, coding bootcamps, hackathons, and transferable skills workshops as part of the MSCA Doctoral Network programme. Based at DTU Wind’s
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expertise in autonomous marine systems. The research focus will be on development, implementation and verification of novel algorithms for motion planning and control of autonomous underwater vehicles. You
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influence its development directly. We are currently evolving our mechanical engineering degree program and constructing labs to support both educational activities and research. Workplace description
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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algorithm. Design methods: Develop novel control methods for power electronic converters feeding electric machine Simulation: Learn advanced simulation tools such as Ansys to simulate and analyze the effect
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tasks will be to: Genetic engineering of bacteria. Phenotypic characterisation of engineered strains. Teach and supervise BSc and MSc student projects. You must have a two-year master's degree (120 ECTS
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Nordisk. The project will explore the correlation between gene dosage, stability and productivity. Further, different approaches aimed at stabilizing genetic constructs, such as genome integrations