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- mdw - University of Music and Performing Arts Vienna
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Field
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project The successful candidate carry out will research in the field of theoretical continuous-variable quantum computation. In particular, the focus will be on bosonic codes, classical simulation
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good knowledge of sociological theories in the fields of music and arts and of empirical research methods Ongoing publication activity and attendance of conference Specific Requirements Knowledge
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on "Canalization and Other Design Principles of Gene Regulatory Network Models" (https://www.nsf.gov/awardsearch/showAward?AWD_ID=2451973 ) and "A mathematical theory for the biological concept of modularity” (https
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that can directly take raw, high-dimensional data from experiments or observatories and rapidly infer theory parameters, such as Higgs boson properties at the Large Hadron Collider or neutron star properties
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mathematical background, including expertise in stochastic optimization (e.g. Markov decision theory and dynamic programming) and applied probability (Bayesian statistics). Excellent coding skills (e.g., in Java
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research. The methods of our investigations are also diverse and complementary, and range from theory and computer simulations to experiments in subatomic physics. The Plasma Theory group within the Division
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candidate to help develop these new manners by which to promote bonds as kernels in the interpretation of chemical simulations. For this purpose, novel theory and simulation software will need to be developed
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; experience with theory driven research with a clear eye for practical implications; a clear interest in collaborative interdisciplinary research; the ability to manage collaborations with partners outside
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profile PhD in Mathematics, Theoretical Computer Science, Information Theory, Physics or related fields High level of mathematical maturity Experience with topics related to quantum LDPC codes and decoding
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properties of Li-rich three-dimensional materials for lithium battery cathodes using density functional theory (DFT), molecular dynamics, cluster expansion, machine learning computational techniques. This work