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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | about 22 hours ago
Dresden University of Technology (TUD) Course location Dresden In cooperation with Dresden University of Technology (TUD) Teaching language English Languages The programme is conducted in English. Full-time
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At the Faculty of Engineering and Science, Department of Materials and Production a position as PhD stipend in Muscle Neuromechanics and Ultrasound Imaging, within the doctoral programme Materials
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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and computational abilities • Demonstrate excellent programming ability in languages such as MATLAB or Python • Excellent communication skills across multiple disciplines • Excellent academic
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similar field; expertise in programming skills and statistical data analyses, including machine learning; affinity with environmental exposure modelling and high-performance computing; strong reporting and
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interest in environmental health and Exposome research; expertise in programming and quantitative data analysis, including machine learning in R/Python; affinity with bioinformatics; strong collaboration
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fusion and multirobot coordination, including multirobot perception, decentralization and mission execution. The RAI team has a strong European and National participation in multiple R&D&I projects. Duties
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fusion and multirobot coordination, including multirobot perception, decentralization and mission execution. The RAI team has a strong European and National participation in multiple R&D&I projects. Duties
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, researchers, patients and activists have formed around environmental sustainability in healthcare; in many instances these span multiple professional groups and organisations. Further research is now needed to
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combine multiple techniques, picking those that complement each other. In particular the use of non-destructive techniques is important, avoiding unintentional sample modifications. Although such “hybrid