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modeling and computational workflows Knowledge about machine learning: statistics and deep learning Experience in data analysis, visualization and presentation Good programming skills in languages such as
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machine learning We offer: Academic freedom to pursue your scientific interests related to infection biology, inflammation, gene expression, and intracellular organization Competitive salary including
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machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
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direction (possibly forming spontaneous “lanes”), crossing, and opposite flows. For single-lane vehicular traffic, the model should revert to a car-following model. In cooperation with the supervisor Dr
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background in (not necessarily all) the following fields: nonlinear PDEs, functional analysis, numerical analysis, PDE-based modeling and numerical simulations excellent command of the English language ability
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are being developed that provide AI-supported tools to identify suitable sources and optimize utilization decisions throughout the product life cycle. Various machine learning approaches are to be used
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research area is the design and analysis of graph algorithms, with possible focus areas including parameterized algorithms, structural graph theory, graph symmetries and similarities, and algorithmic model
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-related concept proposed by Robert Zubrin) or the solar-wind ion focusing thruster. Starting from first-principles and mathematical models, more advanced numerical tools shall be developed to explore
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.) disciplines. GönomiX: Focuses on the evolution of gene regulatory networks and Wnt pathway functions in emerging model organisms (e.g. insects, annelids, snails, flatworms, cnidarians), utilizing ‘omics
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and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team