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correction and fault-tolerance - Quantum optics of trapped ions and Rydberg atom arrays - Numerical tensor network techniques - Topological order and (de)confinement in string-net models - Quantum field theory
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for Biological Cybernetics. The successful candidate will work on a highly interdisciplinary and ambitious research program that aims to apply theory-driven cognitive computational modeling to rich and intensive
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for Advanced Simulation – Data Analytics and Machine Learning (IAS-8) at Forschungszentrum Jülich is dedicated to pushing the boundaries of data science theory and application. Our research spans from use
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thermoacoustic instabilities in hydrogen-fueled combustion systems. The project combines the expertise of 12 European research institutions in advanced experiments, high-fidelity simulations, theory, automatic
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on international or EU-funded research projects Interest in linking theory and practice in higher education contexts Proficiency in German is desirable but not mandatory Funding & Appointment Terms The successful
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literature from 1600 to 1850 and high-quality academic publications are required; expertise in literary theory, cultural studies or comparative (media) studies is desirable. The holder of the professorship is
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, including gas turbines and combustion engines. We combine advanced computational fluid dynamics, theory, machine learning, high-performance computing, and experimental methods to investigate and model complex
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include practical philosophy (e.g. normative ethics, action theory or political philosophy) or theoretical philosophy (e.g. theory of science, epistemology or philosophy of mind). Examples of typical
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Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) | Erlangen, Bayern | Germany | about 2 hours ago
, algebraic aspects of quantum field theory, quantum information, mathematical physics, representation theory, geometry and algebra, and topological field theories. The successful candidate will be able
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will work on a highly interdisciplinary and ambitious research program that aims to apply theory-driven cognitive computational modeling to rich and intensive educational data obtained from learning