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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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the environment, including traffic conditions, travel time, and cost. The project will define the DRL components (states, actions, rewards, policies), select and implement suitable DRL algorithms, and integrate
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, C/C++ and/or Java, etc.; experience with the implementation of specialized transport modelling software, optimization algorithms and procedures; strong ability and desire to learn new programming
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: nabeel.aslam at uni-leipzig.de Web: https://home.uni-leipzig.de/~quantumtechnology/index.php Legal notice: The information on this website is provided to the DAAD by third parties. Despite careful checking
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questions, please feel free to contact Prof. Dr. Münch via email at daniel.muench at uni-giessen.de . JLU aims to employ more women in academic research. We therefore particularly encourage female
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to contact Prof. Dr. Paolo Panza by e-mail (Paolo.Panza[at]uni-giessen.de) Our offer to you Integration into an innovative research project Interdisciplinary collaboration with excellent scientists Opportunity
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. Peter Zaspel via zaspel(at)uni-wuppertal.de. #hiring #uniwuppertal #sciml #scientificmachinelearning
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data Development of algorithms for infection and evaluation of infection hotspots in the plant population Coordination of the scientific interface to the project partners with regard to entomological
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29.05.2025. For further inquiries, please contact Dr Francisco Tenopala or Professor Dr Malte Gather ( apply-to-hcnb@uni-koeln.de ) and take a look at our FAQs.