18 computer-science-programming-languages-"the"-"UCL"-"O.P"-"U.S"-"Prof"-"UNESP"-"Dr" positions at Leibniz in Germany
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strong background in one of the biological disciplines covered by PRIDAS (behavioral biology, data science, neuroscience, physiology, genetics) Knowledge of at least one analytical programming language
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science and industry. The Technische Informationsbibliothek (TIB ) – Leibniz Information Centre for Science and Technology – Program Area C, Research and Development, is looking to employ a Java Developer
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: development and coordination of the wind erosion monitoring program, the development and adaptation of measurement methods and modelling approaches both in the ZALF part of the project and between the involved
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social science degree program (preferably political science, sociology, data science, or a related discipline); at least in the third semester of a BA program or enrolled in an MA Very good skills in
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Computing and Data Science, which is currently being established at JLU. At JLU, the professorship contributes to teaching at a rate of two semester hours per week. You will be responsible for teaching
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tools to evaluate the ecological role of parasites and virus in the Elbe Estuary. The work is carried out as part of the DFG Graduate Program “Biota-Mediated Effects of Carbon Cycling in Estuaries
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opportunities, as well as training in science communication and policy advice – thereby supporting the buildup of geo-economic expertise across Europe. The program is embedded in the Kiel Institute’s broader
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programming experience, but no background in economics—or vice versa—we still encourage you to apply. We are particularly interested in people who are motivated to learn about how research works and to acquire
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of technical documentation. Your profile: A completed university degree (Master's or equivalent) in Bioinformatics, Computer Science, Life Sciences, or a related discipline. Strong expertise in database
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., sensor, field) coordinate and document data flows between citizen-science platforms, AI processing pipelines, and institutional or external repositories to ensure data integrity and traceability implement