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advanced programming skills (e.g., Python, R, or similar) and are comfortable working with large datasets. You have a solid quantitative background, with coursework in Finance and Econometrics considered
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cognitive tasks (Python/MATLAB) Apply computational models of behavior and cognition Analyze high-dimensional datasets (behavioral, physiological, neuroimaging) Publish in leading international journals and
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, retrieval products) Strong programming skills in Python Experience in machine learning, ideally including deep learning architectures such as graph neural networks, transformers, or spatio-temporal models
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university Background or strong interest in mechatronics, optics, electronics with hands-on experience Manual dexterity and careful working style, workshop and/or electronics experience is a plus Basic python
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motivated individual to develop Python tools for analyzing data from our holographic cloud particle imagers. Our research group studies the crucial role of clouds and aerosols in the climate system, aiming
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Python Fluent in both written and spoken English Additional Information Benefits Our institution is based on an interdisciplinary, innovative and dynamic collaboration. You will profit from a systematic
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at international conferences Profile Education: An MSc degree in Geophysics, Physics, Mathematics, Data Science, or a related quantitative field Technical Skills: Strong programming proficiency (primarily Python
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environments Willingness to participate in underground field campaigns Skills in numerical modelling (e.g., fracture mechanics, fluid flow) Strong programming skills (e.g., Python, MATLAB, or similar) Experience
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numerical modelling tools Programming skills (Python and/or matlab required) Willingness to participate in underground field campaigns Ability to work in an interdisciplinary and collaborative environment
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, PorePy, or similar) Programming skills (Python, MATLAB, or similar) Experience with field data and/or underground experiments is an advantage Ability to work independently and lead research activities