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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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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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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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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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The aim of the project is to generate De novo enzymes to degrade PET from composite fibers from recycled textiles. The first-generation designs will be further optimized after experimental
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, probability theory, and combinatorial optimization. Experience in decision-making under uncertainty and autonomous system operation. High level written and spoken English skills. You may obtain further
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research approach is based on classical chemical engineering tools combined with formulation expertise and projects are often carried out, inspired by or in close co-operation with industrial partners. We