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Ref.: 533149 Work type: Full-time Department: Department of Electrical and Electronic Engineering (14300) Categories: Professoriate Staff, Research Staff Applications are invited for appointment as
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datasets using programming languages such as R, SAS, Stata and Python A strong quantitative background in mathematical and simulation modelling, especially Markov-chain, common decision-analytic model
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Discover and characterize novel humoral factors and biomarkers involved in the regulation of metabolic homeostasis Utilize advanced quantitative proteomics platforms such as Olink and Simoa technology to
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solid foundation in field ecology and laboratory-based molecular techniques, as well as proven capacity to lead fieldwork expeditions. The appointee will lead technology transfer and research innovation