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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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for Structural Systems Biology (CSSB). The Department Virus-Host Interaction (Prof. Wolfram Brune) investigates the interaction of herpesviruses (e.g., cytomegalovirus) with host cells, determinants of cell and
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of Tübingen. The project is led by Principal Investigators Dr. Marlen Fröhlich, Prof. Dr. Michael Franke (both Tübingen) and Prof. Dr. Manuel Bohn (Lüneburg). The successful candidate will support the project
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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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here: https://edu.lu/wwpy7 Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas, in collaboration with the Automation and Robotics Research Group, led
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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure
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received after the review date will only be considered if the position has not yet been filled. Position description The Computational Medicine Research Group led by Prof. Pratik Shah at the University
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Regular/Temporary Regular Job Code 9521 Employee Class Grad/Prof Student Position Add to My Favorite Jobs Email this Job About the Job Graduate Assistantship, RIDGS Ethnic Studies Initiative (50% Academic
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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Your Job: At the Electrocatalysis department of Prof. Karl Mayrhofer, we offer a PhD position within the team Nanoanalysis of Electrochemical Processes. Lead by Dr. Andreas Hutzler, the team is