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. This research builds on recent work on optimization-based workspace adaptation in VR/MR and aims to advance interactive systems that dynamically adapt to user behavior, preferences, and intent to optimally
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part in the planning and optimization of new workflows. Close collaboration with other units of the ETH Zurich—particularly the Institutional Research team—will be essential for your success. Beyond your
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novel method for autonomous design of 3D shapes fitting to the user body and optimizing the design to the desired assistance. Apart from actively shaping our group's research, the positions include
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datasets and sophisticated modelling techniques to evaluate and optimize energy systems. We have developed in-house tools and utilize open-source datasets to support our research activities in various
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-transportation system, we are looking for a: PhD Student in Data-Driven Policy Optimization for Transportation and Energy (100%) Project background Our energy and transportation systems are rapidly transforming in
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Intelligence in Mechanics and Manufacturing (AIMM) at ETH Zurich, is offering a position in the field of data-driven optimization. Project background Our research focuses on the development and application
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. The focus is on developing AI-supported, sensor-based solutions for real-time monitoring and optimization of manufacturing processes. These solutions aim to assess process conditions during production
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currently seeking to hire an HPC Optimization Specialist. The objectives of this position are twofold: on the one hand, to extend our HPC user support to help researchers to run their applications and HPC
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We look forward to receiving your application with the following documents as a single PDF: A cover letter indicating which track you are applying for (RL/Optimization, LLM/Knowledge or both) CV
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would build upon the laboratory's past and ongoing work within the context of AI-guided Design, Inverse Design, and Optimization across different application domains. In particular, we are developing