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project examines the key processes, actors and cultural accommodations that drove unprecedented levels of natural resource consumption in industrial societies in the 20th century. Offering an innovative new
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the efficiency and speed of warm rain formation (drizzle) processes under varying natural and seeding conditions. Collaborating with team members on data analysis, interpretation, and modeling efforts. Publishing
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: graph neural networks, natural language processing, algorithmic learning, fault-tolerance, blockchains, consensus, cryptocurrencies, digital money, central bank digital currency, decentralized finance
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(such as JAX/PyTorch/TensorFlow) Strong background in modern AI architectures, especially transformers and multimodal models Experience with computer vision and natural language processing Experience with
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candidate will engage in cutting-edge research in applied environmental microbiology. The research will focus on Microbial Ecology in the Anaerobic Digestion process. The candidate will work as part of
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and on the handling of natural hazards. The Forest Soils and Biogeochemistry research unit investigates the impacts of climate change on soil biodiversity, soil functions, and ecosystem processes
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AI architectures, especially transformers and multimodal models Experience with computer vision and natural language processing Experience with large-scale model training and deployment Knowledge
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synthetic aperture radar (SAR) remote sensing starting in spring 2025. Job description You will join an innovative, highly motivated international research team to investigate advanced SAR imaging algorithms
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: knowledge of basic natural language processing or text entry techniques Familiarity with interactive systems or interaction techniques Strong problem-solving and technical debugging skills Optional
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learning, distributed systems, and theory of networks. Within these three areas, we are currently working on several projects: graph neural networks, natural language processing, algorithmic learning, fault