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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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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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supply chain design, including the application of multi-objective optimization techniques, particularly within the context of biorefineries and biomanufacturing. The successful applicant will also bring
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optimize the impacts of food production, processing and consumption on both the environment and nutritional health, combining nutritional and health sciences with life cycle assessment and absolute
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or passive components into organic substrates; has experiences in magnetic components design, optimization and integration; is familiar with the simulation tools such as Ansys (Maxwell, Q3D, Icepak), LTSpice