182 computer-science-programming-languages-"U.S"-"U"-"U.S" positions at Leibniz in Germany
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program Excellent technical equipment, a wide range of experimental methods and a dynamic and interactive research environment Remuneration according to TV-L, level 13 (65 %), plus annual special payment
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to develop long term, quantitative strategic plans that emphasize sustainable agribusiness enhancement. This PhD position is carried out in collaboration with the Doctoral Program in Agricultural and Forestry
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Excellent command of advanced statistical methods, such as network analyses, using the R programming language Strong publication record relative to the career stage, demonstrating research excellence and
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presentation of collected data and participation in writing scientific publications. YOUR PROFILE: Completed university degree (Master of Science or equivalent) in biology, (bio)chemistry, bioinformatics or a
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networks of functional gene and protein regulation (https://www.ipb-halle.de ). The position is located in the department BPI (Biochemistry of Plant Interactions) and the Program Center for Plant
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Doctoral Certificate Program in Agricultural Economics (www.agraroekonomik.de ) Institutional support to organisation and collection of relevant research data in Kyrgyzstan, Tajikistan and Uzbekistan
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, structured PhD program for all doctoral candidates working at LIV with binding guidelines developed based on the Leibniz Association's guidelines for graduate education. Our program offers multidisciplinary
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-working abilities Excellent communication skills, with proficiency in written and spoken English We offer: You will become part of a world-leading research institute dedicated to the biology of aging and
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extension, in the programme area "Next-Generation Horticultural Systems" (HORTSYS), in the research group "Open Field Horticultural Systems" within the EU-HORIZON project NitroScope - "Scoping European N
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enrolled in a Master’s program in plant sciences, crop science, plant breeding, or a related field. You are interested in fieldwork and data collection. Knowledge or experience with data analysis is an asset