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science, mathematical modelling, data science, transport behaviour, or related fields? Then this PhD position might be the right for you. Ensuring sustainable mobility in dense urban areas is a big challenge faced by
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sensing and responding to the chemical landscape surrounding them as well as the chemical signals inside of them. This project is devoted to gather large data sets to investigate links in olfactory receptor
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(lubricants, gear oils etc.) from machinery like wind turbines. When we want to remove oil droplets, we need them to merge (coalesce) as big drops are easy to remove. Surfactants can either promote or hinder
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in glaciology, Geodesy, Earth sciences, remote sensing, or a related field. Strong skills in data analysis, programming, and handling large geospatial datasets are essential. Experience with satellite
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. Experience within development of biofilters to enhance methane oxidation is particularly relevant. Also, the work entails generation of large datasets, whereby management of such are relevant. You will be part
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outputs in lidar technology and real-time wind-field reconstruction. Expert in wind turbine response analysis. HAWC2 user expert. Demonstrated expertise in data analysis and signal processing with large
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Job Description The microbial community of the world's oceans represents a large and underutilized resource for versatile and robust enzymes with potential technological applications. Despite high
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of large and complex projects Significant proven track record on fundraising Strong publications within the subjects described above. Strong collaboration skills You are expected to take a lead role in
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. If you would like additional information about the position, please contact Head of Fabrication Support, Thomas Pedersen on +45 4525 5833 or thope@dtu.dk . Applications received after the deadline will not