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flow reconstruction, enabling both real-time coarse diagnostics and high-fidelity offline velocity field estimation. Developing reinforcement learning (RL) algorithms for a multi-agent robotics system
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100%, Zurich, fixed-term The Laboratory for Bone Biomechanics (LBB) at the Institute for Biomechanics at ETH Zurich is offering a Postdoc position in multiphoton intravital imaging of heterotopic
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EPFL - Ecole Polytechnique Fédérale de Lausanne, Chair of Stochastic Analysis Position ID: EPFL-POSTDOC [#27659, 1898] Position Title: Position Type: Postdoctoral Position Location: Lausanne
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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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development of algorithms and large-scale numerical simulations. Your expertise will extend to various areas, including quantum Monte Carlo, machine learning, quantum computing, quantum machine learning, and
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the theoretical and algorithmic foundations of AI. A strong commitment to excellence in undergraduate and graduate teaching and mentorship is essential. Preference will be given to candidates who show promise in
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continuously learn from data in a distributed way. Coupling of new theory with effective implementation strategies have the potential to make a lasting impact on building efficiency through sustainable
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, financial networks, e-democracy, voting, social networks, online analysis with delay, and theory of distributed algorithms. In our group, we work on both theory and practice: some members of our group focus
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and dynamics, which we also plan to investigate using AI-based pattern recognition algorithms. In this project, the PhD student will: Run the MIT General Circulation Model (MITgcm) together
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position (technician) will focus on performing Raman/FTIR on retrieved samples. The PhD position will focus on developing a deep-learning algorithm for analyzing the acquired experimental data.