90 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "https:" "https:" "P" uni jobs at ETH Zurich
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executing computational projects. Prior experience with DFT-based electronic structure calculations or other computational quantum-mechanical many-body techniques. Programming skills in either Python, Fortran
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working with multimodal data fusion and high-resolution remotely sensed data is required. Proficiency in programming, particularly in Python, is essential. Knowledge of deep learning approaches and
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in PBF of plastics (whole chain). Develop and test new materials, additives, and processing strategies including printing & testing of parts. Plan and execute laboratory experiments (incl. DoE) with
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and waste-free chemical industry for a sustainable society. Jointly led by ETH Zurich and EPFL since 2020, the research program is funded by the Swiss National Science Foundation (SNSF) and currently
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Sciences with strong IT/programming skills, or in Computer Science/Physics with interest in geoscience and sensors, to support sensor-noise analysis, calibration workflows, and seismic-coverage modelling
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) Familiarity with automation software (e. g. Hamilton Venus), scripting, or workflow scheduling (e.g. HighRes Cellario) and experience with standard programming languages such as Python, C++, Matlab or R
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, Deep Optics Excellent problem-solving abilities and a passion for research Strong programming skills and proficiency with differentiable simulation frameworks are a plus Excellent verbal, written, and
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modeling and teaching duties. Position details: Start date: February 1st, 2026, or by agreement Fully funded PhD position (approximately 4 years). Final admission to the doctoral programme follows a
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a highly committed multidisciplinary team Regular meetings and close collaboration with the project partners Enrolment in the PhD program of ETH Zürich ETH Zürich is a family-friendly employer with
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The NOMIS Foundation–ETH Fellowship Programme supports postdoctoral researchers at ETH Zurich within the Centre for Origin and Prevalence of Life (COPL). The programme is intended to foster