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Theoretical physics and mathematical physics aims to understand the physical world from first principles. The prominent methods in this area include quantum field theory and string theory. You will
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fundamental theory of emergence from an information theoretic perspective. You will work on a new mathematical framework to identify and characterize emergent information structures in multivariate data
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mathematics. Many of the problems within the project are motivated by questions in statistical physics and/or theoretical computer science. You are expected to actively look for opportunities, motivations and
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field theories The mathematical definition of probability distributions for random functions, measures or distributions is not straight-forward. Random functions are defined with the help of Kolmogorov’s
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Energy Markets. This role is perfect for someone who not only has a strong foundation in stochastic modeling and computational finance but is also eager to apply these mathematical/computational techniques
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combine wet- and drylab approaches aiming to identify key regulatory genes and metabolites for optimized plant defence production. As a PhD student you will be involved in the mathematical modeling
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modelling based on graph theory and population balances, mathematical tools describing changes of molecules on a coarse-grained level. The Random Graph approach is further developed to further increase
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for the master's programmes in Chemistry, Mathematics, Stochastics and Financial Mathematics and Physics & Astronomy, in which currently at around 900 students are enrolled. The education is provided by lecturers
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(such as mathematical theorem proving and/or declarative constraint-based reasoning). What are you going to do? You will be expected to: complete and defend a PhD thesis within the official appointment
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general mathematical framework for explainable decision making and introduce models to provide explanations for different classes of optimization problems. Solution algorithms will be developed and tested