346 machine-learning "https:" "https:" "https:" "https:" "https:" "The Francis Crick Institute" positions in Switzerland
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- ETH Zurich
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-read sequencing data analysis is highly desirable. Familiarity with signal processing or applied machine learning is advantageous. You should demonstrate strong motivation to develop innovative
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dynamical systems, and machine learning, with applications to synthetic biology and biomolecular circuit design. Our research develops mathematical and computational frameworks for understanding and
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Systems.”Funded through an ETH Zurich Career Seed Award, this project aims to develop scientific machine learning frameworks that integrate physics-based modeling with neural network architectures. The goal
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of cutting-edge tools, models, and strategies to understand and engineer immune systems for translational medicine. Candidates may use integrative approaches that combine immunogenomics, machine learning
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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
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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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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knowledge and technology from research to Swiss machine, electrical and metal industries. The research group Control and Automation at inspire AG offers the following position in collaboration with Bota
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Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to advance our existing algorithms that reconstruct 3D garments from multi
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thinking with a structured, quality-focused approach to data and methods. Ideally, experience in one or more of the following: data engineering, building data-driven apps, computational linguistics, machine