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. You should have a strong academic background in engineering, applied mathematics, or computer science, combined with a clear interest in scientific programming, machine learning, and data analytics
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focus is demonstrating how predictive analytics can improve maintenance and production planning. By comparing data-driven and traditional methods, the project will highlight the tangible benefits
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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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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
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environmental engineering. A collaborative and analytical mindset, with the ability to synthesize complex information across experimental and theoretical domains. Enthusiasm for advanced electron microscopy
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(e.g. C++, Python, Matlab) OpenFOAM (beneficial, not required) Strong analytical and problem-solving skills. Approval and Enrolment The scholarship for the PhD degree is subject to academic approval, and
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Engineering, respectively, will be important. You are expected to actively contribute to joint research projects, experimental design, and data interpretation across disciplinary boundaries. Responsibilities
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in the Danish energy sector. As a PhD candidate, you will join the Energy Markets and Analytics (EMA) Section within the Division for Power and Energy Systems (PES). The EMA Section is renowned for its
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on enzyme kinetics and stability measurements. The team have access to labs equipped with alternative reactors and excellent analytical equipment. Responsibilities and qualifications The position includes
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advances in automation, analytics and data science, has fundamentally changed the scope and ambition of harnessing the potential of biological systems. Big data approaches and analysis of biological systems