18 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "U.S" uni jobs at Swedish University of Agricultural Sciences
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information about the department visit: www.slu.se/aquatic-sciences Read more about our benefits and working at SLU by visiting: https://www.slu.se/en/about-slu/work-at-slu/ Location: Uppsala Form of employment
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and administrative staff. For more information about the department visit: www.slu.se/aquatic-sciences Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu
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advanced levels, mainly within the agronomy- soil & plant programme, and is also active in courses for professionals. Together with a research group from the Department of Applied Animal Science and Welfare
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. For more information about the department visit: www.slu.se/aquatic-sciences Read more about staff benefits and life as an SLU employee on https://www.slu.se/om-slu/jobba-pa-slu/ Read more about third-cycle
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they gain experience during the programme. Your profile You have a degree as a Veterinarian from an approved education in Sweden or another EU/EEA country or in Switzerland, and have the right to work
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generate conversations between people and pave the way for science, creativity and development. Where to apply Website https://web103.reachmee.com/ext/I017/1114/main?site=6&validator=107666e3b6b77a4
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. Qualifications Applicants must hold a Master’s degree in molecular biology, cell biology, genetics, plant biology, or a related field, and have documented wet-lab experience, familiarity with computational
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representatives: https://internt.slu.se/en/my-employment/employee-associations/kontaktpersoner-vid-rekrytering/ The Swedish University of Agricultural Sciences (SLU) has a key role in the development
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to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Doctoral Candidate position in Biomedical science with specialization in parasitology Description: Current diagnostic methods, coprological
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Infrastructure (SBDI) and maintains the Swedish Species Observation System. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes