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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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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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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
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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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-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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characteristics, assessments committees’ configuration and process) and 2) the resulting outputs for applicants depending on grant decisions. The research will leverage artificial intelligence (AI) to optimize
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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
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the waste material from coating production and coating use. Test methods Reliable and fast test methods to optimize coating performance is of utmost importance in coatings development. We work on new test methods and
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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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within computational modelling, optimization and integration of thermal energy storage technologies – such as large water pits and phase change material storage. You will work with colleagues, and with