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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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impact and societal role of the Department of Mathematical Modeling and Machine Learning (DM3L). The future assistant professor tenure track will supervise PhD students and contribute to teaching and its
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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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at the Department of Biosystems Science and Engineering (D-BSSE) of ETH Zurich in Basel invites exceptional candidates to apply for a PhD position in pioneering projects at the intersection of synthetic biology
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methods and approaches are needed to better tackle the challenges posed by increased uncertainty and complexity. Machine learning (ML) and artificial intelligence (AI) methods have shown promise
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at the Department of Biosystems Science and Engineering (D-BSSE) of the ETH Zurich in Basel invites exceptional candidates to apply for a PhD position in pioneering projects developing synthetic biology-inspired
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) Contribute to the strategic direction of research Publish high-impact research in leading journals and present findings at international conferences on energy systems and machine learning Collaborate with
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. • Familiarity with machine learning, dimensionality reduction, clustering, and statistical modeling. • Strong communication skills, interest in interdisciplinary work, and ability to train students and postdocs.
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foundations of conversational AI as well as domain knowledge on how and why it can be deployed effectively. You should have knowledge and skills in both data analytics (e.g., machine learning, statistics