9 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S"-"U.S" positions at Empa
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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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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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-based optimization, enabling autonomous measurement campaigns and real-time data assimilation. This research combines fluid mechanics, artificial intelligence, and robotics to establish the foundation
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) influence system performance and trade-offs. The research will combine analytical modelling with data-driven and AI-based methods, for example for scenario generation or uncertainty exploration. The PhD will
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Ph.D. Position in Organic Chemistry, Polymer Chemistry, and/or Sol–Gel Chemistry & Materials Science
interpreting experimental data Contributing to patent applications with support from the team Leading scientific publications and presenting results at international conferences Occasional travel to the industry
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development of electrochemical sensors detecting environmental pollutants, providing real-time information for effective management. Past and current work includes electrochemical sensors for airborne virus
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Characterize aerogel and aerogel composites Compile, analyze, and critically interpret experimental data Contribute to patent applications with support from the team For up to 20% of your time, contribute
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models and in vitro assays. Experience in phototherapy, programming and large data analysis is a plus. Excellent communication skills and fluency in English (written and oral). Our offer The project is
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lab models for evaluating coating stability, durability, and antimicrobial efficacy Integration of coating and biological performance data to guide optimization of multifunctional coatings. Your profile