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analysing big amounts of various types of data, e.g. geospatial, tabular, image/video/sound. Experience in passive acoustic data collection, processing and analysis. Experience with complex and large data
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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
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variable and climate-sensitive ecosystems, which poses great challenges for their mapping. You will be part of a research project aiming to unravel the complex interactions within peatland ecosystems using
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characterization (e.g. NMR), biofilm extracellular polymeric substances, biophysics, glycoconjugates, complex assembly, or lectins, is an advantage. Your profile Applicants should hold a PhD in glycobiology
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professional collaborative skills and a broad academic network which you bring into play in your contribution to the academic development of Aarhus University and its profile both nationally and internationally
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researchers, policymakers, industry partners, and farmers who translate complex data and modeling outcomes into practical insights. As the chosen candidate, you will be critical in contributing to the main
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-field between sustainable chemical processing, food waste valorization, biopolymer development, and characterization, and complex heterogeneous reaction system. The research focus should cover
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successful candidate with a strong research profile on linking food structure studies in complex food materials with processing in relevant environments and properties of food products, who would like