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candidate will undertake the following activities: - Synthesis and characterization of catalysts: Develop hybrid materials (metals, oxides, or composites) optimized for the selective formation of aldehydes
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research environment involving several PhD students and postdocs, and strong regional and international connections, with collaborations with the University of Geneva and CERN. Terms of Employment
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, abandonment, comments, peer interaction) Formalization of algorithms for orchestrating educational AI agents : Train RL and LLM agents and study multi-objective optimization (mastery, well-being stability) Work
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). Expected results: • New HWCVD technology validation and optimization. • Obtain high optical performance a-SiC thin films (test material in small dimension, <2-inch) to be used in other WPs. • Comprehensive
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. Combining field-level data with other data available in the cloud, such as weather data and food pricing models allow to further optimize smart farming. Among the most impactful operations for sustainable
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thin films. Technical difficulties remain however for the realization of optimal epitaxial layers, in accordance with this new approach and able to withstand a voltage of 1400 V. The proposed thesis will
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of chemical compounds (NMR, GC-MS, IR, X-Ray). The student will also have access to modern optimization methods for catalytic systems, such as highthrouput experimentation (HTE, collaboration with the HTE
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system. To achieve this, the PhD will combine: instrumental development (optical optimization, illumination strategies, multi-camera synchronization), optical modeling (contrast mechanisms in phase