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to the adaptation of the Environmental Noise Directive for these new technologies. Your main focus will be to develop machine learning-based drone noise models that will be able to generate an accoustic footprint
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and Data Analytics, Fraunhofer-Chalmers Centre E-mail: mats.jirstrand@fcc.chalmers.se Phone: +46 730 794303 Where to apply Website https://academicpositions.com/ad/chalmers-university-of-technology/2026
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's doctoral program (https://www.ntnu.edu/nv/phd) PLEASE NOTE: For detailed information
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Code7491StreetHøgskoleringen 1Geofield Contact City Trondheim Website http://www.ntnu.no Street Høgskoleringen 1 Postal Code 7491 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket
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Max Planck Institute for the Study of Societies • | Koln, Nordrhein Westfalen | Germany | about 18 hours ago
you will learn the specific methods you need for your project Feedback from experienced research advisers Excellent research facilities Instruction in English Thesis may be written in English or German
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supervised by a multidisciplinary team of academic and societal experts. Detailed descriptions of the work packages and their interconnections are available on the DECIDE website https://decideproject.nl/ We
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of biology First practice in scientific writing and with molecular-genetic research methods Didactic skills / experience in e-learning Strong IT user skills, including MS Office and other programs e.g
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, eager to learn more about Flanders, Belgium and the Netherlands. Learning Dutch University Language Centre (@ Ghent University) In-Gent https://www.in-gent.be/voor-jou/nederlands Stad Gent Read more
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training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process . An excellent technical infrastructure
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differences in learning, memory, and processing between these systems. This project develops the necessary methods to study how smart AI-models are compared to people, now and in the future, and sheds light on