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environment spanning real-time graphics, large language models, and affective computing Regular 1-on-1 mentoring and weekly team meetings Collaborative, international team at ETH Zurich's Computer Graphics
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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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, 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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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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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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scripting, high performance computing, or advanced statistics and data analysis frameworks (python, R) Regardless of background, the successful applicants will have an interactive personality, motivation
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: Must hold a master’s degree in computer science, data science, or a closely related field Have strong analytical and problem-solving skills Are able to work independently and take ownership of technical
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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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data lakes with large-scale natural ETAS simulations and synthetic datasets to provide the foundation for AI training Scientific Communication: Publishing findings in high-impact journals and presenting