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research in the broad field of computational methods for the built environment. Particular emphasis is placed on building information modelling, digital drawings, point cloud capturing and processing as
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“PhD application for Self-supervised Learning of Time Series Data” in the subject line. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally
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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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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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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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16.07.2025, Wissenschaftliches Personal A PhD position (75% TV-L E13, to be extended to 100% after 8 months) in discrete optimization is available at the Professorship of Optimization and
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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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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
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• Experimental investigations using atomic force microscopy (AFM), including force-distance curve-based imaging, (single molecule) force spectroscopy, nanomechanics, and associated data analysis • Application
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robotic sample retrieval system that will be able to obtain surface swabbing samples of critical infrastructure buildings for chemical or biological analysis. The cohort of PhD students are spread around