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- Łukasiewicz Research Network - Krakow Institute of Technology
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Field
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investigate how sensor data can be fused to improve navigation, obstacle awareness, vehicle state estimation, guidance and mission reliability. Propulsion-control co-design: Studying the coupling between
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productive academic team with a strong international network covering radiochemistry, radioecology, environmental chemistry, nuclear waste management and environmental modelling. The successful candidate will
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potential cause of coating irregularities (waviness) and rejection of the final product. In this project, we will apply combined experimental, theoretical, and computer simulation studies to bring detailed
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. Job requirements MSc degree in Hydrology, Environmental Engineering, Civil Engineering or a related field Excellent computer programming and GIS skills Proficiency in written and spoken English (Dutch
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://www.nnrc.uio.no/english/index.html The PhD candidate will be part of a dynamic and productive academic team with a strong international network covering radiochemistry, radioecology, environmental chemistry
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Neurosciences Computer Graphics and Ecological Informatics Computer Networks Computer Security Databases and Information Systems Data Fusion Data Science Infrastructures Didactics of Informatics Digital
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of the transregio. To this end, the college provides training opportunities, guidance & a pleasant networking environment in order to assist the research progress of doctoral students towards graduation without
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the Faculty of Engineering, plus those housed in Plant Biosciences at the Sutton Bonnington campus. Data sets will be generated using simulated and experimental data and these will be used to train networks
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successful candidate, you will benefit from membership in the TUM Graduate School, be embedded in an active international scientific network, and present your results at national and international conferences
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professor from the natural sciences and a professor from information/computer/mathematical science. The DASHH graduate curriculum comprises 18 ECTS and is divided into the following branches: knowledge gain