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Project Description We invite applications for a fully funded PhD position in experimental proteomics. The successful candidate will contribute to a fundamental research program exploring chemical
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electric fields to polarize interfaces and drive induced-charge electro-osmosis, reorganizing ion clouds faster than diffusion. Quantify time-dependent zeta potentials and Debye lengths to switch double
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2026 or as soon as possible thereafter. We expect Degree. A two-year master’s degree (120 ECTS) in Robotics, Electrical Engineering, Software Engineering, Computer Science, or an equivalent field (or a
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aspects of cheminformatics. The position is founded by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases ”, led by Prof
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information about entering and working in Denmark here . Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it
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obtained by holding a position as a postdoc for at least three years. You have experience in various international projects with different stakeholders. As an ideal candidate, you should also: Have a strong
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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PhD fellowship at the Copenhagen Center for Glycocalyx Research at the Department of Cellular and Mo
leader in the field of membrane biology and glycosciences. We are composed of several research groups and host about 20 postdocs and 20 PhD students, in addition to master’s students and guest researchers
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning