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Postdoctoral Researcher in Semantic Knowledge Engineering & Interoperability in Materials Science in
research institute under the Federal Ministry for Economy and Energy, we conduct research, testing, and provide consulting services to protect people, the environment, and property. Our work in materials
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 3 months ago
in quantitative MRI or ultra-high-resolution imaging Interest in neurodegeneration or brain metal homeostasis We offer the possibility to conduct truly fundamental research to change the field
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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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Postdoctoral Position in Computational Humanities to Research the Macroevolution of European Literat
Max Planck Institute for Empirical Aesthetics (MPIEA) | Frankfurt am Main, Hessen | Germany | 3 months agoresearch at the intersection of the humanities and social sciences; Fluency in written and spoken English; Strong teamwork skills; Proven ability to independently design and conduct computational studies
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for integrated energy systems. Your tasks in detail: Analyze the impacts of future energy transition pathways on the planning and operation of European power and gas infrastructures, and evaluate system behaviour
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with sub-Kelvin cryogenic techniques Strong aptitude for mentoring students Good communication skills A strong drive to conduct ambitious, cutting edge research towards scalable quantum computing A
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. Microorganisms in the gut microbiome play a key role in health and disease, yet their behavior in complex and dynamic microenvironments remains poorly understood. Within a Helmholtz collaboration, we are
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adults actively seek, select, and evaluate information to learn about the world. The lab combines behavioral, computational, and cross-cultural approaches to study curiosity, exploration, and reasoning
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, reliability, and consistent behavior. Learning-based controllers can achieve high performance in complex and uncertain environments, yet ensuring predictable operation under distribution shifts, sensor noise
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-advertising auctions. The economic properties of such systems are still poorly understood. In general, learning procedures in game-theoretic problems can exhibit cyclic behavior or even lead to chaotic dynamics