194 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"University-of-Huddersfield" positions in Switzerland
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of ETH Zurich, which not only supports your professional development, but also actively contributes to positive change in society We are actively committed to a sustainable and climate-neutral
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Structuring and follow-up of project ideas Execution and coordination pre-studies Preparation of industry and grant proposals Development of collaboration opportunities with other research groups Development
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in management and organization research, not a technical AI-development role. The successful candidate will study AI as an organizational and strategic phenomenon, with a strong focus on theory-driven
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affect technology adoption, industrial development, policy design, and its socio-technical and political feedback effects. The project is embedded within ETH Zurich’s new Einstein School of Public Policy
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. Empa is a research institution of the ETH Domain. The Urban Energy Systems Laboratory (UESL) pioneers strategies, solutions, and methods to support the development of sustainable, resilient, and
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opportunities for professional and personal development. Start date is May 2026 or upon agreement for a duration of 2 years. We live a culture of inclusion and respect. We welcome all people who are interested in
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manufacturing and operations to support development, integration, test, launch, and on-orbit commissioning Provide on-orbit or mission support, including anomaly resolution and telemetry evaluation
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; Astronomical Instrumentation; Optical Design Skills Development During the PhD, the student will develop expertise in: Extreme-precision radial velocity (EPRV) instrumentation Optical design and tolerance
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Observations; Stellar Variability; Time-Series Analysis Skills Development During the PhD, the student will develop expertise in: Ground-based exoplanet transit surveys Operation, installation, and commissioning
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crucial insights. In this project, you will contribute to the development of AI-driven methodologies for experimental fluid mechanics , focusing on: Designing multi-fidelity neural networks for adaptive