326 assistant-professor-computer-science-data Postdoctoral positions at Nature Careers
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-record within the field of observational research. Experience with programming is preferred, and some experience with data science or AI will be considered a strength. Further, the candidate should
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, production efficiency, and milk production. Contact Further information on the position may be obtained from Head of research unit, Professor Peter Lund, phone: +45 4015 7673, email: Peter.Lund@anivet.au.dk
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Two year postdoc position at Aarhus University for single molecule FRET based investigations of l...
molecules. The project is based in the team of professor Gregers Rom Andersen at the department of Molecular Biology and Genetics (MBG). Funding for the project is secured by a major grant from the Novo
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University, Ole Worms Alle 3, DK-8000 Aarhus C. The affiliation will be with the Department of Agroecology. More information can be obtained from Professor Tommy Dalgaard (tommy.dalgaard@agro.au.dk , phone +45
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, the Postdoctoral Researcher will be in charge of Assisting Professor Neframi in coordinating the Doctoral Training Unit on Green and Digital Transitions in the Single Market (DTU-GREITMA) Assisting in organizing
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application includes: A detailed CV (incl. information about IT/computational skills) A one-page letter of intent describing your motivation for this position, how your research experiences and interests
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research on the topic outlined above is paramount Candidates are expected to be interested in working at the boundaries of several research domains PhD degree in computational biology, bioinformatics
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The place of work is Aarhus University, Campus Ole Worms Alle 3, 8000, Aarhus C. The affiliation will be with Land-CRAFT, Department of Agroecology. More information can be obtained from Assistant Professor
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with the Department of Agroecology. Contact information More information can be obtained from contact to Associate Professor Martin Thorsøe (martinh.thorsoe@agro.au.dk ) and or Assistant Professor Morten
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interpretation. A Ph.D. in biostatistics, statistics, bioinformatics, computational biology, or computer science is required. Strong computational background with programming and visualization skills in R and