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, adapt locally to users and environments, and remain computationally efficient. These models will be explored and benchmarked in software, with selected approaches translated into embedded prototypes
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crucial insights. In this project, you will contribute to the development of AI-driven methodologies for experimental fluid mechanics , focusing on: Designing multi-fidelity neural networks for adaptive
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Marie Skłodowska-Curie doctoral training network “SPACER", which is made up of 21 partners. A total of 17 doctoral candidates will work in this project over a period of 36 months. School: School
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This doctoral thesis is part of the European Marie Skłodowska-Curie doctoral training network “SPACER", which is made up of 21 partners. A total of 17 doctoral candidates will work in this project over a period
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Network with 15 funded 3-year PhD positions in parallel. Your profile Master Degree in environmental/natural sciences or engineering, or similar. Experience with developing computational models Preferably
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networks. Extension of the findings to microwave systems is also planned. The research outcomes are expected to be published in major specialized and broad-audience journals. Profile You are expected to have
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-Education/Academic-Programs/Graduate-Center.html ) offers various training formats for PhD students and organizes networking events. Finally, Basel is a mid-sized Swiss city, well connected and offering a
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and flow field interactions Tuning of the CFD models with experimental results Artificial Neural Network training and development Scientific publications in journals and at conferences Supervision
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 4 hours ago
leaf or VOC samples), plant-insect interaction studies or ALAN research. Moreover, you are comfortable using statistical software, preferably R. Fluency in speaking and writing English is essential
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and mateRials, fabrication techNologies for the responsible co-creation of future Sustainable integrated electronic systems), an EU MCSA Doctoral Network with 15 funded 3-year PhD positions in parallel