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innovative methods to leverage machine learning for numerical weather forecasting and climate modeling. Project background We are looking for a motivated Machine Learning Scientist to join the development team
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innovative methods to leverage machine learning for numerical weather forecasting and climate modeling. We are looking for a motivated Machine Learning Scientist to join the WeatherGenerator project. Like
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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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interested in applied machine learning and computer vision at the intersection of research and industrial deployment. Job description Develop and implement state-of-the-art computer vision algorithms
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Thermal effects are a major source of geometric errors in modern machine tools. Accurate prediction of temperature fields inside machine structures is therefore essential for improving machining
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Center for Project-Based Learning. The successful candidate will contribute to research at the intersection of embedded machine learning, signal processing, and smart sensing systems, with applications in
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Armed Forces. The research contributes to the scientific foundation of monitoring and rapid altering systems for underground infrastructure. Project background Seismic and fiber-optic sensing technologies offer
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programming skills in Python Experience with machine learning systems or LLM-based architectures Experience working with complex data systems or developing applied AI prototypes Familiarity with modern AI tools
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to assess ecosystem services Evaluation of plant phenotyping models, jointly with the other Work Packages of PhenoMix Statistical analyses, including machine learning approaches Presentation at national and
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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