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. theses at the interface between structural engineering and machine learning. You will disseminate your research through peer-review publications and participation in international conferences. You will
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performance of remanufacturing processes by providing data-driven material assessments and validation techniques. Responsibilities and qualifications You will join the Section of Materials and Surface
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performance computing numerical methods in our state-of-the-art open source micromagnetic model, MagTense. MagTense is based on a core implemented in the Fortran programming language, and it relies
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that also act as green energy producers driving the societal transition towards net zero. In this position, you will build on your expertise in IoT and low-power computer and communication systems to research
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articles and through participation in national and international conferences, is an integral part of the job. You will also be expected to take some responsibility for guiding and training students in
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wastewater discharge. WaterGreen, the newly funded IFD Grand Solution project, aims to transform biogas plants’ process water into ultrapure water for green hydrogen production while recovering valuable
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industrial partners. The working language is English, and we pride ourselves on a diverse, inclusive, and inspiring workplace that fosters personal and professional growth. What we expect We are looking for a
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, consisting of (a) remanufacturing processes, (b) take-back systems, (c) design for disassembly and circularity, (d) business models, and (e) sustainability and circularity assessment. The project will analyse
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digital co-simulation platforms (e.g., Modelica-Python/Simulink) Applying machine learning and data-driven approaches to enhance the operation of district heating substations Participating in course
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for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment