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                for degradation? At the core of mRNA nuclear export works an evolutionary conserved machinery centered on a large protein complex: TREX. While we recently uncovered a mechanistic framework of the core of this 
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                , their achievements and productivity to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, the Chair of Algorithms offers a position as Research Associate 
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                experience in the use of mass spectrometry • Good working knowledge in the application of statistical analysis procedures • Sound knowledge of ecological and evolutionary concepts • Basic knowledge in the use 
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                experience in the use of mass spectrometry • Good working knowledge in the application of statistical analysis procedures • Sound knowledge of ecological and evolutionary concepts • Basic knowledge in the use 
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                position (contract-based) and one PhD fellowship in Computational Biophysics/Chemistry (see also https://constructor.university/comp_phys). The PhD position is focused on efficient algorithms 
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                research in a variety of areas in biology and computation, with possible specializations in genomic and molecular biology techniques as well as in algorithms, statistics and artificial intelligence 
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                for traceability, robustness, and physicochemical correctness Implement and adapt the most promising algorithms to model radionuclide migration in crystalline host rocks Execute proof‑of‑concept ML simulations and 
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                Master’s degree (or equivalent) in Biology, Chemistry, or a related field. A strong interest in evolutionary biology, behavioral ecology, and chemical ecology. Excellent communication skills in English, as 
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                algorithms to compute similarity between interaction interfaces across millions of comparisons. This hinders identification of novel modes of protein binding, i.e. those predicted by AlphaFold, and it hinders 
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                play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms