48 parallel-computing-numerical-methods PhD scholarships at Technical University of Munich
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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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in Earth Observation develops innovative methods for information extraction from remote sensing data in close cooperation with the Department EO Data Science of the Remote Sensing Technology Institute
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of the doctoral project is positively evaluated after the first two years. CMS’s inter-disciplinary team is performing research in the broad field of computational methods for the built environment. Particular
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full-time PhD candidate on the topic of “Automatic Recognition of building attributes” About us The TUM-Professorship for Data Science in Earth Observation develops innovative methods for information
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determine vent morphology and where organic molecules accumulate. Measurements will inform your numerical simulations of vent remodeling and transport within the vent. Your project is embedded in
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28.07.2023, Wissenschaftliches Personal Prof. Karen Alim’s group on Biological Physics and Morphogenesis at the TUM Campus Garching uses theoretical and experimental methods to investigate how flow
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-disciplinary research unit, which provide bioengineering solutions to urgent societal needs. CBI scientists develop next-generation imaging and sensing methods to measure previously inaccessible properties
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. Candidate´s profile: • Master’s degree in Life Sciences, in Computational Biology or MD degree • Previous research experience in immunology • Experience in flow cytometry, cell culture and in high-dimensional
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affiliated with the research group “Science & Technology Policy” of Prof. Dr. Ruth Müller. About the research project: The project “Science as a field of struggle: a multi-method empirical study of inequality
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21.12.2021, Wissenschaftliches Personal The Department of Computer Science, Technical University of Munich, has a vacancy for a PhD candidate/researcher position in the area of efficient algorithms