134 parallel-computing-numerical-methods-"Simons-Foundation" positions at Leibniz in Germany
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, or green technologies We expect Master’s degree in agricultural economics, environmental/resource economics, industrial engineering, business informatics, or a related field Demonstrated interest in agent
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master's or diploma degree in computer science or mathematics already successfully completed doctorate confident demeanor and proficient use of German and English (both equivalent to at least B2) expertise
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an interdisciplinary framework as part of a joint research program. What will be your tasks? We are seeking a highly motivated candidate to join the newly established Collaborative Research Centre “Carbon Sequestration
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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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-analysis techniques, causal inference and quasi-experimental methods is a strong asset; Familiarity with reference management tools (e.g., Zotero, Mendeley) and systematic review tools (e.g., EPPI, Covidence
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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or comparable content management systems We expect: the ability to work independently and on your own initiative a methodical and systematic approach structured and goal-oriented thinking capacity to familiarise
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this knowledge gap and establish improved GHG models accounting for soil invertebrates. To achieve this, we create a rich AI-training dataset for multi-modal inferences, combining computer-vision, environmental
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Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the
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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