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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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small-scale processing sector. By joining this project, you will contribute to the development of AI-powered tools that predict non-compliance, improve food safety monitoring, and ultimately protect
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and enjoys working with complex, multi-disciplinary topics. In summary, the main tasks of the PhD position are: To perform research in power systems balancing with a focus on European power and energy
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equivalent to a two-year master's degree Extensive and demonstrable experience (through publications or thesis work) with multi-parametric flow cytometry Experience with isolation and culture of human
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working with “DTU Smart Road,” a full-scale pavement research platform at DTU’s main campus that hosts embedded strain and temperature sensors. Experiments will also involve the development and installation
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the past years, DTU Chemical Engineering has made significant investments in digitalizing our experimental infrastructure, including a large-scale pilot plant and the Coatings Science and Technology
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optimization. Experience with energy system modeling - ideally of large scale multiple country energy systems, PtX and renewable fuel production. Strong writing and presentation skills. A willingness and desire
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prior experience in at least three of the following areas: Python programming Develop LLM-based tools to automate data connector generation for data ingestion. Design and implement a multi-layered storage
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and exact optimization methods enhanced by machine learning (ML). The overarching goal is to solve large-scale combinatorial optimization problems more efficiently, particularly in domains such as
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English and interpersonal skills for working in a multi-disciplinary team environment. Willingness to engage in group work with a multi-national team; Able to work independently; Approval and Enrolment