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how perishable biological products, such as vaccines, react inside cold chain unit operations and to pinpoint why some products decay faster. For that purpose, we develop digital twins of the cargo
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some products decay faster. For that purpose, we develop digital twins of the cargo, based on measured air temperature and humidity data in cold chains by commercial sensors, and deploy them in end
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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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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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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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is the development ferroelectric lead free ceramics sintered below 500°C and the analysis of their mechanical and electromechanical properties of elastomers with piezoelectric properties using 3D
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of Zurich and Wageningen University & Research. The four-year STEPS project focusses on developing data-driven and machine learning methods to monitor CO2 and NOx emissions using the upcoming satellite
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Laboratory for Air Pollution / Environmental Technology, in collaboration with the University of Zurich and Wageningen University & Research. The four-year STEPS project focusses on developing data-driven and
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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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. Your profile Master Degree in environmental/natural sciences or engineering, or similar. Experience with developing computational models Preferably some experience with LCA, MFA, Risk Assessment, green