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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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of Excellence. A willingness to acquire externally funded projects, supervise doctoral candidates, and engage in interdisciplinary collaboration is required, as is an active commitment to open science practices
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to application at http://www.kseta.kit.edu/application.php . Further information about the KSETA Europe application procedure, available research topics, subjects for doctoral dissertations and the KSETA
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Description For our location in Hamburg we are seeking: Doctoral Researcher in Machine Learning and Data Processing in the Field of Seismic Measurements Remuneration Group 13 | Limited: 3 years
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for improved understanding of structural and kinetic processes in electrolytes; and machine learning concepts for improved analysis of experimental and simulated data. Material Synthesis Within this research
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on research fields, such as Neurosensory Science and Systems (University of Oldenburg) https://uol.de/en/phd-neurosensory-science-2 Auditory Sciences: Physics and Engineering, Physiology and Therapy of Hearing
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estimation, causal discovery, and concept-based explanation techniques Integration of causal and XAI methods into machine learning pipelines within the CRC 1294 “Data Assimilation” Implementation, evaluation
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cooperation partners in their research projects with state-of-the-art light and electron microscopes (https://www.leibniz-fmp.de/cellular-imaging ). We work with proteins, cell cultures, and model organisms
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in
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from the date of defense of your PhD and until September 9, 2026. Career breaks (parental leave, military service, work outside research, etc.) do not count towards the amount of research experience must