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students. Beyond their talent, these classmates share a desire to shape the future through technology, insight, intellectual exploration, and community service. Job Description: Research Assistant Professor
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of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied
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enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education
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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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Previous Job Job Title Research Assistant Professor of Biomedical Engineering – Neurodegeneration Focus Next Job Apply for Job Job ID 368288 Location Twin Cities Job Family Academic Full/Part Time
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. You may obtain further information from Professor Kim Guldstrand Larsen, Department of Computer Science, email: kgl@cs.aau.dk concerning the scientific aspects of the stipend. PhD stipends
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As a PhD student within the Economics Division, you will have access to a broad programme of research training opportunities. These include advanced methods courses, data skills workshops, and an
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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | about 10 hours ago
Dresden University of Technology Course location Dresden In cooperation with Dresden University of Technology Teaching language English Languages The programme is conducted in English. Full-time / part-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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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