93 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" "P" positions at ETH Zurich in Switzerland
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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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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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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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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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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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, 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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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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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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, ACHIEVE consortium The primary focus of this role is to serve as the Knowledge and Technology Transfer (KTT) Expert within the ACHIEVE consortium as part of the SWEET funding programme of the Swiss Federal