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conceptual framework linking nanoscale features to macroscopic adsorption efficiency. Generate and curate high-quality datasets to support data-driven materials optimization and future integration with AI
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conflict. This may involve formation control, adaptive trajectory planning, and real-time vehicle communication to avoid interference and optimize coverage. Control techniques and sensor fusion will be
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on generating new knowledge for optimizing biological conversion of carbon dioxide to acetic acid in close collaboration with an industrial end-user of the developed technology. Responsibilities and tasks Your
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platforms can unify production environments, enabling predictive maintenance and data-driven optimization through centralized data platform architectures. Your research will focus on addressing current
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optimization of novel organic reactions, as well as substrate scope investigation including isolation and characterization of products. You must have a two-year master's degree (120 ECTS points) or a similar
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reagents, development and optimization of novel organic reactions, as well as substrate scope investigation including isolation and characterization of products. You must have a two-year master's degree (120
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optimization of SERS substrates, Raman measurement, data analysis, and validation of results with reference methods such as high performance liquid chromatography (HPLC). You are expected to have a solid
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-objective optimization, and online decision-making approaches are relevant areas of expertise for this position. Previous experience with developing models, tools, or processes is desired. The candidate has
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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of samples. To apply and further optimize data analytical workflows. A comprehensive database will be created, documenting the key chemical and physical properties of advanced bio-oils. The qualified applicant