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machine learning methods to monitor CO2 and NOx emissions using the upcoming satellite missions (e.g., CO2M, TANGO, Sentinel-4/5). Your research will contribute directly to monitoring global efforts
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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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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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will: Develop novel and robust catalytic materials for efficient removal of emerging contaminants in water. Learn and apply advanced materials characterization techniques. Work with different analytics
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including a letter of motivation, CV, diplomas with references and contact details of two reference persons. Please submit these exclusively via our job portal. Applications by e-mail and by post will not be
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-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2025/phd-student-in-safe-and-sustainable-… Requirements Research FieldEngineeringYears of Research
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, certificates, diplomas and contact details of two reference persons. Please submit these exclusively via our job portal. Applications by e-mail and by post will not be considered. Where to apply Website https
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via our job portal. Applications by e-mail and by post will not be considered. Where to apply Website https://academicpositions.com/ad/empa/2025/phd-position-in-the-field-of-cold-si… Requirements
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of catalytic coatings for water treatment. As a PhD candidate, you will: Develop novel and robust catalytic materials for efficient removal of emerging contaminants in water. Learn and apply advanced materials