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setups, large-scale data acquisition and analysis, FPGA programming skills, and knowledge of Python and C++ are important assets. The project is highly interdisciplinary (microtechnology/electronics
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phenomenological and quantitative first-principles theory of static and dynamic chirality in crystalline materials. The specific sub-project advertised here seeks to understand the unexpectedly large measured
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apply for third party funding. Contributions to teaching within the Engineering Geology group are also expected. Profile PhD in Data Science, Computer Science, Mechatronics, Remote Sensing, Engineering
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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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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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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