25 senior-lecturer-distributed-computing Postdoctoral positions at Leibniz in Germany
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and spatial distribution” in the Research Unit Coastal Seas and Society until the 30.11.2027 and a percentage of 100% (40h/week), subject to the funding of the project. Remuneration is paid in
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Postdoctoral Researcher (m/f/d) in Cognitive Psychology / Computational Neuroscience to be filled as soon as possible. The position is limited to 3 years and can be extended for another 3 years. Your task
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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves
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identifying climate-resilient restoration sites in the Baltic Sea. The project integrates regional climate modeling, AI-driven simulations, and biogeochemical modeling to predict seagrass distribution under
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and mainstream Climate and ESG financial risk assessment at supervisory authorities in the EU, we are looking for a researcher/senior researcher to join the team. The project is funded by the European
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modeling, AI-driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based
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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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; to support the department’s ongoing work, for example, by organising lectures and conferences; involvement in citizen science projects; to link your project with the research conducted in the »Knowledge and
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: completed scientific higher education degree (PhD) in the field(s) of Earth system science, physics, climate physics, geosciences, mathematics, computer science or a comparable field demonstrated experience
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems