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and simulation tools. Research topics include geometric modeling of engineering products, methods of geometric analysis, methods of Building Information Modeling, modeling and simulation of construction
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, natural hazards management or related fields Interested in protective forests and their management Good quantitative skills (e.g., data analysis, simulation modelling, remote sensing) Good communication
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privacy-preserved fashion. Research topics include, but not limited to, i) handling distributed DL models with data heterogeneity including non i.i.d, and domain shifts, ii) developing explainability and
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Forschungsinstitut and aims to reconstruct global 3-D coastal sea surface height by combining long-term satellite altimetry, high-resolution SWOT mission data, tide gauges, and ML approaches. The position offers
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hardware is developed in cooperation with Heidelberg university. Data analysis, writing and publishing research articles, and presenting at topical conferences/workshops are an integral part of this project
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08.09.2021, Wissenschaftliches Personal The Professorship of Machine Learning at the Department of Electrical and Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13
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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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application-oriented research that unlocks the potential of data through rigorous analysis – advancing solutions in societally relevant domains. Your profile Master’s degree in Statistics, Industrial
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or for multiobjective optimization problems. Implement the developed algorithms (e.g., in Python) and evaluate their practical performance on artificial and/or real-world data. Teach tutorials (in English) for
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission