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Field
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Reconfigurable/Spatial computing architectures, such as FPGAs, CGRAs, and AI accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs
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framework across a suite of practically relevant optimization problems in public transport planning and airport operations. The broader project also includes research on heuristic methods, in particular Large
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starting date is November 2025. The topic of the PhD project will be theoretical research in discrete optimization, with a particular focus on either graph algorithms or multiobjective optimization
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improves the performance of ROMs, making them more applicable to real-time structural health monitoring, vibration analysis, and control design. This research offers real-world impact across several
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The Faculty of Engineering, Research Group FLOW, is looking for a PhD-student with a doctoral grant. More concretely your work package, for the preparation of a doctorate, contains: Research: The
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
possess sufficient breadth or depth of knowledge in the discipline and of research methods and techniques to work within own area. The candidate will also have the ability to continually update knowledge
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)chemical basis of plant resilience and performance in challenging environments related to climate change. The IPB offers excellent research facilities and state-of-the-art infrastructure to study the
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or discrete probabilistic structures is beneficial but not required. What we offer: WIAS Berlin is a premier research institution known for its strength in optimization, optimal control, dynamical systems, and
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contributing positively to a collaborative research environment. Desirable: experience with building energy or power system applications, cooperative or coalitional game theory, or high-performance computing
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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure