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of distributed computing, machine learning, image and text analysis, randomized data structures, high-performance computing, and quantum algorithms. Beyond this research, we aim to support computational thinking
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environment. We are creative, we shape technology, we design products, we improve processes, we open up new paths. Our clients value our modelling competence, algorithms and software products. We
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data define data and publication formats developing matching algorithms for simulated vs. observed data supporting proposal writing to secure future project funding Requirements: sound communication and
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and/or statistical algorithms to classify building and land-use types relevant to electrical consumption Label and prepare training data for AI models; develop automated pipelines for classification
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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure, improved mechanical and corrosion properties. Research stays are planned
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sensitivity analysis, impact of the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy
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to develop automated algorithms for downscaling drivetrain components for specific test purposes. Furthermore, you will perform multiple case studies to analyze the performance of the developed scaling methods
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for the discovery of new physics experiments) Developing, benchmarking and advancing state-of-the-art AI-driven exploration, optimization, and search algorithms in extremely complex and enormously large spaces
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potential projects: Development of modern auto-differentiation (JAX-based) physics simulators for the discovery of new physics experiments) Developing, benchmarking and advancing state-of-the-art AI-driven