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applications for a non-tenure track Assistant/Associate Research Professor, Biology and Management of Urban Pests. The successful candidate will engage with the national pest management industry and conduct high
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conferences; Mentor BSc/MSc students. About NL2120 NL2120 is a program in which science, business, nature organizations and education work together to gain knowledge about natural solutions (Nature-based
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background, we will invite at least one applicant from each of these categories to an interview. Contact information For questions about the position: Professor Nina Reiners, Norwegian Centre for Human Rights
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of forests in climate change are now key social issues that require more knowledge. In order to both sustainably use and safeguard forest biodiversity, a coherent basic science research program is needed
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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | about 20 hours ago
Dresden University of Technology (TUD) Course location Dresden In cooperation with Dresden University of Technology (TUD) Teaching language English Languages The programme is conducted in English. Full-time
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to impactful, data-driven research with a global perspective, and help improve healthcare systems and address inequalities. Under the supervision of Professor Maarten J. IJzerman and co-promoter Dr. Nora Franzen
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at https://www.cbs.dk/en/research/phd-programme . For further information please contact Head of Department Professor Mitchell Dean, e-mail: mde.bhl@cbs.dk Information about the department can be found
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organisations. The extensive educational programme is based on academic research conducted within the faculty of Law, Economics and Governance. Students are trained to be highly qualified, internationally
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Applications are invited for two Research Assistant / Research Associate posts on the project EQUATE - a project that investigates how Natural Language Processing (NLP) could be made globally more
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, Industrial Engineering, Computer Science, or Machine Learning. Solid experience with quantitative optimization methods, including (but not limited to) mathematical programming and stochastic dynamic