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for multimodal inferences, combining computer-vision, environmental parameter measures and DNA data. Your role will be central in data acquisition and foremost machine-learning models creation. You will
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, holistic strategies, processes, as well as structures for collaboration, governance, and learning are co-designed and implemented jointly with stakeholders, employing innovative methods and tools to foster
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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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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
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research and scientific methods relevant for research in behavior and ecology. The unique opportunity to gain field experience in a West African national park, train with experienced behavioral biologists
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Leibniz Association. The following position is available at the Institute subject to approval by the funding organization from October 1, 2025, for a fixed term of three years, in the program area "Next
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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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-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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work together, in order to learn from one another and generate new knowledge and new methods to create a better quality of life in our world. DWI offers you a wide range of possibilities to develop
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work together, in order to learn from one another and generate new knowledge and new methods to create a better quality of life in our world. DWI offers you a wide range of possibilities to develop