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field interactions Tuning of the CFD models with experimental results Artificial Neural Network training and development Scientific publications in journals and at conferences Supervision of students Your
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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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missions (e.g., CO2M, TANGO, Sentinel-4/5). Your research will contribute directly to monitoring global efforts to reduce greenhouse gas emissions and achieve net-zero targets. Your tasks Simulate emission
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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
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-culture approaches, and skilled in fluorescence microscopy and image analysis for functional read-outs of microphysiological systems Software: Proficiency in Python, MATLAB, or R for data analysis, and
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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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Materials Science group at ETH Zurich within the framework of the Marie Skłodowska-Curie Actions – Doctoral Networks (MSCA-DN) RE-Fibre project . Project background of the Re-Fibre Project RE-Fibre is a
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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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, 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