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Field
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within trusted digital environments. Their research focuses on ontology-driven conceptual modelling, FAIR data stewardship, and model-driven system/service engineering, dealing with data-driven services
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plumes from point sources using the MicroHH atmospheric model. Analysis of plume dynamics and NOx chemistry in the high-resolution simulations. Develop and refine data-driven methods for emission
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. You will be working at the intersection of battery modelling and algorithm development, with a strong emphasis on the data-driven modelling and control aspects. You will contribute to shaping
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pursuing a doctoral degree in Computer Science, Electrical Engineering, or Telecommunications and Information Technology Engineering. Must have knowledge of software development, event-driven business
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programming (e.g., Python, MATLAB). Energy system modelling expertise with experience in academic research Preferred Skills: Educational background in Electrical Engineering, Computer Science, Renewable Energy
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, computer science, software/systems engineering, and data science. Experience with NLP/LLMs and/or requirements engineering is highly desirable; familiarity with model-based systems engineering, safety-critical
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of battery modelling and algorithm development, with a strong emphasis on the data-driven modelling and control aspects. You will contribute to shaping the technologies that underpin a more sustainable and
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include a research proposal aligned with one or more of the following priority areas: Research Themes Multiphysics and data-driven constitutive modelling of traumatic brain injury and its long-term impact
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Three PhD positions at TU/e in collaboration with Canon Production Printing, combining polymer science, rheology, and computational modeling to create the inks and coatings of tomorrow. Information
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Start Date: Between 1 August 2026 and 1 July 2027 This project aims to frame hypersonic aerodynamics as a grand inverse problem. By combining modern state-of-the-art AI (foundation models, physics