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at the Institute of Physical Chemistry studies structure and dynamics of molecular processes. We apply static and time-resolved vibrational spectroscopic methods. To strengthen our team, we are looking for a PostDoc
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data, stochastic optimization, modern machine learning methods, scalable algorithms for advanced Machine Learning techniques and explainable AI. In teaching, the position will contribute, inter alia
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research, teaching and departmental administration. Your profile: Completed doctoral/PhD studies in the field of Cultural and Intellectual History of Premodern South Asia (Indology) or a related discipline
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methods from both Mathematics and Physics, complemented by concepts from Theoretical Computer Science. The group is located jointly at the Faculty of Physics – as part of the Quantum Optics, Quantum
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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 program
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better understand our world. Does this sound like you? Then join our accomplished team! Your personal sphere of influence: We are looking for a highly motivated and hardworking Prae Doc (PhD student) for 4
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. Visual Data Analysis you will develop methods/tools to enable more effective research, e.g., enabling medical professionals to explore and discover patterns in disease progression and to assess treatment
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both older and more recent literary history. Ideally, they are experienced in interdisciplinary co-operation and have an interest in the methods and theories of literary research. They are also
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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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developmental biology, chromatin, RNA and chromosome biology, and synthetic/computational methods (including AI/ML) that will address complex biological questions from a mechanistic angle. Together with IMP, GMI