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) processes and develops methods and algorithms to achieve a fundamental understanding of high-dimensional data and processes in the bioeconomy in particular. Bioinformatics at Forschungszentrum Jülich plays a
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position is the development of novel machine learning methods for modeling molecular properties, in particular regression models for bi-molecular properties. The research is embedded in the thematic context
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Student (f/m/d) in Quantum Algorithms for Droplet and Bubble Oscillation Dynamics Modelling. Your tasks Development and implementation of numerical and algorithmic methods for the simulation of fluid
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machine learning (ML) along with data from previously solved problem instances to solve new, yet similar, instances more efficiently than with general purpose algorithms such as Newton`s method. In
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Functional Theory (DFT) Familiarity with artificial intelligence methods Good knowledge of electronic structure methods Experience with Linux, Git and related tools Knowledge in the field of high-performance
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excellent research opportunities due to the University, three Max Planck institutes, the University Hospital, and Europe’s largest AI research consortium. You can find out more about Tübingen here: https
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combines state-of-the-art computational multiscale modelling (using DFT/TDDFT methods, collision theory, molecular dynamics, stochastic dynamics, Monte Carlo and analytical methods) and its thorough
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Remember to check that your application is complete and meets DAAD requirements before submitting! Otherwise your application cannot be considered. DAAD will conduct a formal review of the applications
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spectroscopy will be a key component of the experimental toolbox. Where appropriate, additional techniques such as diffraction or photon-based methods and microscopy methods (scanning tunneling microscopy
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biological techniques, as well as animal models, will be applied. We offer: Embedding in an internationally competitive scientific environment An established, broad spectrum of scientific methods A wide range