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monitoring will be based on real time data streaming from the machine numerical control. The project will cover all the aspects related to the implementation and automation of the tool life cycle management
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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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conceptual framework linking nanoscale features to macroscopic adsorption efficiency. Generate and curate high-quality datasets to support data-driven materials optimization and future integration with AI
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Job Description If you are ready to launch your research career in advanced manufacturing and want to build cutting-edge skills in AI and real-time data-driven production, this PhD opportunity is
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the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's
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The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the
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scientific backgrounds, including electrical engineering, industrial engineering, operations research, data science, and applied mathematics. Many of our former students are now successful scientists in both
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internationally recognised academic environment with over 400 employees and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering
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Job Description We are seeking a talented and highly motivated PhD student to work in the field of transient astrophysics with a special focus on large transient surveys in the era of big data