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Responsibilities: The successful applicant will cover research and teaching in the field of data-driven material research with a reduced teaching load of two weekly credit hours at Freie Universität Berlin. The professorship includes the opportunity of establishing and leading a newly founded...
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using the programming language Fortran. Experience or willingness to run numerical models on parallelized supercomputers. Experience in the analysis of model output using Python or a similar high-level
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CRC 1114 aims at methodological developments for the modelling and computational simulation of complex processes involving many (more than two) interacting scales, driven by real-life applications
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program, which includes tailored training, workshops, retreats, and conference travel. You will have access to cutting edge laboratories, individual supervision, and a wide range of development
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theoretical and practical experience with machine learning methods, especially for training of machine learning potentials - development and utilization of ab initio electronic-structure methodology - previous
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The MODAL research campus ("Mathematical Optimisation and Data Analysis Laboratories") researches and applies modern mathematical methods and data-driven approaches to develop innovative decision
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of accounting, corporate reporting in a national and international context, and auditing issues. Methodologically, the focus is on quantitative empirical approaches, in particular computer-aided text analysis
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: economic sociology, historical sociology, (historical) political economy, historical social science, computational sociology - advanced skill in quantitative, statistical methods (R, stata, Python), ideally
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languages used: C++ 2014, CUDA, Lua Desirable: - interest in high-performance computing with graphics processors (GPUs) and simulation methods - fluent knowledge of modern C++ and a scripting language
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), and computational modeling (deep neural networks). We apply multivariate analysis methods (machine learning, representational similarity analysis) and encoding models. Job description: This is an open