77 model-driven-engineering-"Data-driven-Materials-Modeling" PhD positions in Denmark
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Aalborg University, Department of Energy, Campus Esbjerg, invites applications for a three-year PhD Stipend from October 1st or soon hereafter in dynamic modelling, simulation and optimization
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systems, large language models, agentic AI, or scientific software development, especially in industry or research settings. Strong software engineering skills, proficiency in Python programming, experience
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of computational modelling of battery materials and fabrication and electrochemical investigations of new battery materials and complete battery cells. Responsibilities and qualifications For decades, battery
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Department of Food Science (FOOD KU), Faculty of Science (SCIENCE) invites applicants for a PhD fellowship in Food Engineering, “Linking Powder Structure to Performance” The project is in
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Architecture, Mechanical Engineering, or aclosely related discipline. A strong background and demonstrable interest in hydrodynamic numerical modelling are essential. The candidate is expected to have experience
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mathematical models at the bedside, often resulting in spin-off companies and products. Qualifications: Applicants should have a master’s degree with a mathematical/engineering background, preferably but not
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In this PhD position, you will help design the next generation of circular plastics systems by combining hands-on polymer processing with data-driven modelling. The PhD study is a full-time, fixed
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Communication sciences Information science Engineering » Communication engineering Engineering » Electronic engineering Mathematics » Applied mathematics Mathematics » Probability theory Mathematics » Algorithms
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programme Wireless Communications; as per January 1, 2027, or as soon as possible thereafter. In electronic engineering, Aalborg University is known worldwide for its high academic quality and societal impact
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system configurations, experimental setups and operational data. The scientific ambition is to develop methods that combine physical models and data-driven approaches for adaptive, real-time operation of