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departments and faculties at the University of Vienna, whose focus lies on theory and applications in the field of data science and machine learning. The Faculties of Mathematics and of Computer Science, which
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astrophysics, and uses a variety of approaches, such as stochastic processes, kinetic theory, variational analysis, finite element methods, and data-driven techniques. The Vienna School of Mathematics doctoral
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prior exposure to modern developments in biomathematics and will also have a solid knowledge of mathematical analysis, partial differential equations as well as kinetic theory and will be able to take
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the network architecture need to be to capture the solution accurately? In essence, we’re exploring the frontier between modern machine learning and classical mathematical theory—where neural networks meet some
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administration The research should focus on data mining, e.g., clustering, representation learning, causality detection and graph mining. This is part of your personality: Master in Computer Science, Applied
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flows such as entropy dissipation. This is a chance to tackle cutting-edge mathematical and computational problems with real-world relevance, using modern approximation theory and machine learning
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with graph learning, in particular using graph neural networks (evidenced by publications in top-tier journals or conference proceedings). Excellent and up-to-date knowledge of typical machine learning
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group “Foundations of Cryptography” within the research group “Theory and Applications of Algorithms” at the department of Computer Science focuses on provable security of cryptographic schemes. We
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) Mathematics, or a related discipline (Statistics, Econometrics) Knowledge in analytical research methods, such as game theory, information economics, or microeconomics Excellent command of written and spoken
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the time the position begins) in Science and Technology Studies or related discipline; • Broad knowledge of the topics, theories, and methods of Science and Technology Studies; • Distinct research