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improve high-throughput experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and
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experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and components to automate
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. Olga Fink ). IMOS develops advanced machine-learning and AI methods for complex engineering and industrial systems, with a particular focus on improving their reliability, availability, and operational
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colorectal tumors. Specifically, the work will focus on optimizing 3D X-ray virtual histology methods by phase-contrast micro-CT and corresponding image processing techniques also with view on combining it
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-flow UV-Vis, to quantify mediator-booster reactivity and component dissolution during operation, developing a firm understanding of how material formulation and experimental parameters govern charge
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machine-learning and AI methods for complex engineering and industrial systems, with a particular focus on improving their reliability, availability, and operational performance while enabling more
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, to quantify mediator-booster reactivity and component dissolution during operation, developing a firm understanding of how material formulation and experimental parameters govern charge transfer at the liquid
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datasets with multi-omics profiles of tumors from previous studies Developing new machine learning models through collaboration with the Swiss Data Science Centre Establishing data analysis pipelines
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building of charge and ion transport processes in functional materials. Synthesis and processing of ceramic proton conductors, solid electrolytes and semiconductor photoelectrodes Structural characterization
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. Empa is a research institution of the ETH Domain. The Laboratory of Advanced Materials Processing (LAMP) is a multidisciplinary research unit that develops innovative functional modification of materials