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100%, Zurich, fixed-term The postdoctoral researcher will advance the application of AI, large language models (LLMs), and machine learning to extract trustworthy climate information from large
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journey, from the collection and management of data to machine learning, AI, and industrialization. With a large multidisciplinary team of professionals across three locations (Lausanne, Zurich, Villigen
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, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU), the PhD student
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to efficiently train on the large, densely-connected and graph-structured data encountered in our systems of interest. Your contributions would be across the spectrum from methodological development
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the approach of Large Language models, the aim of the WeatherGenerator is to build a so-called foundation model for Weather and Climate. The model will be trained on various model data as well as many
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datasets The position is limited to two years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep
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operating and advancing the data platform, assist interdisciplinary projects that integrate multiple data sources, and use high-performance computing resources to manage and process large environmental
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running data-driven or hybrid hydrological models Strong programming skills (ideally in Python and/or R) Experience in working with large datasets, ideally hydrological, meteorological or climate
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of hybrid AI-optimization modelling. This position focuses on the design of AI-based surrogates of large-scale energy system models and will be integrated in the activities of the Nexus-e group with close
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AI & LLM Systems Project background We are looking for a Senior Research Engineer to build next-generation AI systems that bring large language models into real-world manufacturing environments. In