223 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"Simons-Foundation" positions in Switzerland
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benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits chevron_right Working, teaching and research at ETH
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) distributional generalization, transfer learning, causality Multi-objective settings and alignment, RL theory Statistical learning theory, optimization (e.g., implicit bias) Robustness (broadly defined), privacy
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change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits
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Mixed Reality. This research combines physiological time series analysis (specifically EMG during muscle activation), machine learning, and real-time system design for intelligent interaction systems
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benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits chevron_right Working, teaching and research at ETH
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, which not only supports your professional development, but also actively contributes to positive change in society. You can expect numerous benefits , such as public transport season tickets and car
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position in the area of Machine Learning for Engineering Design under the guidance of Prof. Mark Fuge, the Chair of Artificial Intelligence in Engineering Design. The general area of the laboratory covers
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degree in Machine Learning, Data Science, or Biomedical Informatics. 5+ years of experience in software product development and management, preferably in healthcare or life sciences. Proven ability
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. Profile Applicants must hold a M.Sc. Diploma (120 ECTS points) or equivalent in civil, mechanical or electrical engineering, geosciences, physics, applied mathematics, computer sciences or related fields
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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