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background in microfabrication. Further, experience with experimental setups, large-scale data acquisition and analysis, FPGA programming skills, and knowledge of Python and C++ are important assets
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learning (RL), such as (but not limited to) Theory of online learning, reinforcement learning, and data-driven control Learning in games, and multi-agent RL RLHF and alignment in LLMs Representation learning
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12 Feb 2025 Job Information Organisation/Company ETH Zürich Research Field Engineering » Electrical engineering Engineering » Materials engineering Physics » Other Researcher Profile Recognised
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decline at a large scale, linking these metrics with forest composition. This role involves employing data fusion methods, integrating forest structural characteristics, climatic, and topographic variables
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, and large industry partners. Advising PhD and Master’s students will be an integral part of your role. You will also be involved in some of the group’s teaching activities and gain experience leading
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Analyzing experimental data and optimizing protocols This position is full-time, with flexible starting dates in 2025. Profile A PhD degree in physics or relevant fields Prior experience in experimental
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of the calculations are executed on GPUs, with the storage of intermediate data on CPUs. The Computational Nanoelectronics Group of ETH Zurich recently started implementing a novel device simulator called QuaTrEx