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. The Researcher is involved in multiple research projects at a time and employs a research-practice partnership framework to work closely with local community organizations in areas such as non-medical drivers
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that can be validated with experiments and bottom-up models at multiple scales in order to predict the macroscopic response. Hence, this research will investigate the degradation of metallic materials under
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from on-board and off-board sensors have been collected and analysed. However, such raw data collected from multiple sensors is often disturbed and does not indicate the ship performance at calm water
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engineering skills and at least some experience with common collaborative development tools: git, GitHub, CMake, Docker, Spack, gtest, ctest, etc. You are pragmatic and take initiative; your analytical skills
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abilities, and an analytical mindset. We are seeking a candidate with the following qualifications: A strong academic record, with foundational knowledge in entrepreneurship, sustainability, innovation
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Description As part of the German government's artificial intelligence (AI) strategy, the successful Saxon competence center ScaDS.AI Dresden/Leipzig (Center for Scalable Data Analytics and
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are identified as (novel) key analytes for perfusion monitoring. The described goals reflect that this project contains both experimental and computational activities. Research groups This project will be co
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analytical skills for model formulation and optimization Demonstrated research potential, ideally with a track record of publications in relevant venues (journals such as IEEE T-ITS, INFORMS Transportation
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center ScaDS.AI Dresden/Leipzig (Center for Scalable Data Analytics and Artificial Intelligence) is being expanded into a leading German AI competence center for Big Data and Artificial Intelligence (AI
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to the body of knowledge by enhancing the safety, relia- bility, and efficiency of automated vehicles by developing a collaborative multimodal perception system. This system leverages data from multiple sources