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recycling. You will develop material characterization and process-evaluation methods for end-of-life PV modules, assessing recovery yield, purity, energy consumption, environmental impact, scalability
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, several lab-scale flow battery test stands, 3D printers for rapid reactor prototyping, and equipment for electrode and composite fabrication. Analytical facilities include X-ray diffractometers, UV
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Your tasks Conduct research on user modeling and coordinate selected research activities within CREST-AI together with Prof. Christina Niklaus. Combine LLM reasoning with neuro-symbolic NLP to build
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combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038/s41467-025-63947-5 https
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combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038/s41467-025-63947-5 https
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advanced computational modeling, mathematical modeling, or experimental psychology. Profile We thrive on interdisciplinary collaboration. You should hold a PhD in musicology, computer science, cognitive
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preprocessing, feature extraction, statistical modeling, visualization and documentation. Implementing advanced statistical and computational analyses, including trial-level models, mixed-effects
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methodological and focuses on developing new generative modeling approaches, scalable training algorithms, and foundation model technologies. The role is suited for candidates with a strong machine learning
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characterization of indoor aerosols and other air pollutants, including source-resolved measurements; Modeling of indoor pollutant emissions, transport, transformation, and exposure, ranging from mechanistic or
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a related quantitative field Experience with machine learning and/or statistical modeling applied to biological data Proven expertise in single-cell data analysis (scRNA-seq and/or scATAC-seq