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the use of machine learning for regression tasks. Demonstrated proficiency with Python or similar scientific programming environment. Ability to work with large datasets, develop reproducible workflows and
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an environment of respect, belonging, and access for all. We demonstrate Courageous Integrity through setting exceptional standards and acting in the best interest of our communities. We are encouraged to Be
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position at the interface of scientific Computing and Artificial Intelligence for applications pertaining to fluid mechanics of turbulent and environmental flows starting September 1, 2025, or as soon
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should be willing to participate in animal experiments. We offer The Neurotechnology Group at ETH Zurich provides one of Europe’s leading research environments for neurotechnology and drug delivery. Our
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-disciplinary environment? Information Many of the most challenging problems in science and engineering involve physical systems that evolve over time while exhibiting rich mathematical structure. Fluid flows
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engines for unmanned aircraft systems (UAS), and sustainable aviation fuels for urban air mobility (UAM). The candidate will work in a multidisciplinary environment consisting of PhD-level scientists
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and will be expected to contribute to a safe, collaborative, and results-oriented research environment. The work will emphasize process engineering, experimental systems, and data-driven evaluation
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thrusts. Good programming and analytical skills, and willingness to work with new technologies/systems. Excellent communication skills and the ability to work effectively in a collaborative environment. For
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science and polymer engineering, developing next-generation materials for complex engineering environments. Working within a collaborative interdisciplinary team spanning materials chemistry and civil
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highly collaborative environment including teams in Neutron Sciences Directorate and Physical Sciences Directorate, leveraging state-of-the-art neutron characterization and other characterization tools