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Description Two PhD positions in atmospheric selenium research: field & lab analyses and process-based modeling We are seeking two highly motivated and curious PhD students to join the Inorganic Environmental
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, machine learning, and statistical modeling on cutting-edge datasets in precision feeding, animal behavior and welfare, multi-omics and environmental impact. Join our interdisciplinary team to drive real
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it fit to run on a supercomputer. You will apply your newly developed simulation tools within different research projects. This new position is embedded in the international research project LION 2 on
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Researcher or experienced Data Scientist to harness AI, machine learning, and statistical modeling on cutting-edge datasets in precision feeding, animal behavior and welfare, multi-omics and environmental
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at the intersection of engineering and economics to develop and apply energy system models to diverse energy systems and research questions. The Chair holder’s joint appointment as the Head of the Laboratory of Energy
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on studying shape parametrization, learning gait optimization functions for mechanism design and using different machine learning embeddings (such as GANS, VAEs, and Diffusion Models) for developing a new full
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by two ETH professors from two different departments. If you don’t have hosts yet, Design++ can help match you based on your proposal. Project background You are a great fit if you’re excited to: (a
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and backtests to assess model performance and estimate the tool's real-world impact. You will have regular check-ins with the project team at Stanford but will conduct the day-to-day data work yourself
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CV as a single PDF file. What we offer Work-Life Balance Flexible working models (such as part-time positions, mobile working, job-sharing) Childcare at the kihz foundation of UZH and ETH More Learning
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with ex situ experiments, demographic modelling or handling large datasets as well as holding a valid driver's license is a plus. Application / Contact Please upload your application via our online