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econometric time series analysis, focus group discussions, and a choice experiment. Hence, we seek a candidate having expertise with some of these methods, and interest and capacity to learn the others. It is
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to: Collect data through e.g. literature studies regarding the raw materials to be used Perform data analysis and interpret results from chemical and microbial analysis of the raw materials Carry out product
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of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts are supported by
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and reduction of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts
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, if they hold a PhD degree and have not lived in Denmark the last 10 years. The position is covered by the Job Structure for Academic Staff at Universities 2020. For further information, please contact: Associate
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successful candidate will have previous experience in computer science or data science, with a PhD and publications in at least one of the following areas: Formal modelling and verification of business
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and technicians to solve analytical challenges and develop, optimize, validate and apply analytical methods to evaluate food safety. Key Responsibilities - Perform trace-level analysis of organic
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heterostructure quantum devices Perform electrical measurements (i.e. magnetotransport) at room and/or cryogenic temperatures Participate in TEM and nano-ARPES characterisation and analysis Collaborate with project
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quantitative data collection and analysis. We’re looking for a colleague who is passionate about the research topic, highly organized and able to work independently, and able to work collaboratively in
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Analysis of CO2-to-Food Pathways The ideal candidate should have all or several of the following academic and personal qualifications: A PhD in chemical engineering, process systems engineering, energy