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: Engineering design & CAE (e.g., structural/thermal/fluids workflows) Chemical and process industries (e.g. optimization, control, surrogate models) Related computational engineering problems where simulation
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Lehrstuhl für Angewandte und Computergestützte Mathematik | Aachen, Nordrhein Westfalen | Germany | 5 days ago
Dissipative Dynamics, the international research training group Modern Inverse Problems, the SNuBIC research unit, the Sparsity and Singular Structures collaborative research center, as well as with the School
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of internationally visible, foundational research in AI-driven semantic structure extraction, automated reasoning-flow modeling, and adaptive content generation. The research focuses on methods for analyzing and
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optimization. Together with a dedicated partner from bioinformatics you will first survey pairs of drug discovery application problems and corresponding quantum algorithms, before you focus on promising
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on developing advanced methods for semantic structure extraction, conceptual and argumentative flow reconstruction, rationale-aware content generation, metacognitive prompting, and adaptive personalization. Core
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enabled to participate in relevant international scientific conferences. Together, this structured training programme is designed to optimally prepare you for a successful career. If you don’t have the
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generation, sequence analysis, and data management Rapid Evaluation of newly emerging computational tools relevant for protein design Implementation and optimization of experimental workflows for rapid protein
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: At FBN, you will be welcomed by a dedicated, multidisciplinary team. We will support you with a structured onboarding. We will also help you with any questions you may have regarding your arrival in
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(courses are offered). Structured and systematic working style and ability to work cooperatively in international teams Our Offer: We work on highly topical, socially relevant issues and offer you the
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sensors, actuators, transducers, etc. Fundamental knowledge of the structural mechanisms behind electromechanical coupling will allow for their systematic exploitation and go beyond the empirical approaches