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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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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-learning models on distributed systems
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deep learning (segmentation and foundation-model architectures) Demonstrated ability to design and execute technical projects Scientific independence with clear interest in biological mechanisms and
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of novel physics-guided AI algorithms for drug design, integrating physics-based modeling with state-of-the-art deep learning methods. The project will focus on creating a next-generation docking framework
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heating and cooling, storage, and local electricity grids. A key goal is to translate methodological innovations in deep learning into practical tools for sustainable urban energy systems, supporting
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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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deep learning workflows for tree species mapping. The position contributes to building a scalable system for forest monitoring by refining model performance and ensuring high quality geospatial data
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) Unsupervised machine learning and deep learning methods Analysis, visualization, and interpretation of learned design spaces Contributing to research outputs (prototypes, publications, open-source code) Profile
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an annual budget of 17 MCHF and about 170 researchers and collaborators, Idiap is today a key Swiss research institute in multiple AI fields, including machine learning (including deep learning, foundation
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multiple AI fields, including machine learning (including deep learning, foundation models or agentic AI), human-centered AI (including social computing, multi-modal processing or robotics), digital security