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-focused , contributing primarily to one of the following projects: Project A – Synthetic Data for Theory-Driven Behavioral Research This project investigates how large language models (LLMs) produce
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(e.g. R or Python), statistics, machine learning, and data science. A good publication record with respect to your career stage and research interests in climate impacts in mountain regions complete your
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utilization. The successful candidate will play a significant role in the EU‑funded TIMBERHAUS project (www.timberhaus.eu). Your tasks Develop machine learning models and computer vision algorithms for wood
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of the following projects: Project A – Synthetic Data for Theory-Driven Behavioral Research This project investigates how large language models (LLMs) produce synthetic responses to psychological experiments and how
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understanding of WS/DP adsorption to solid–water interfaces, including soils, sediments, sludge, and model mineral/organic surfaces. Experimental studies will investigate polymer–surface interactions, adsorption
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, computational quantum many-body physics, and machine learning The Quantum AI lab at ETH (Prof. Juan Carrasquilla ) invites applications for postdoctoral positions to work at the intersection of computational
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seek candidates with strong skills in programming (e.g. R or Python), statistics, machine learning, and data science. A good publication record with respect to your career stage and research interests in
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and resilient materials and structures. By combining numerical modeling, laboratory experiments, and theoretical analyses, we seek to link microscopic processes with the macroscopic behavior of both
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Previous experience with in vivo animal models is advantageous Excellent communication skills in English (oral and written) are a must High motivation, strong interest in skeletal research, durability
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modelling and AI/ML for the quality monitoring/control, at the end offering to the society novel nanostructured materials, their shape-forming and integration into devices. Your tasks We are seeking a highly