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tasks (Python/MATLAB) Apply computational models of behavior and cognition Analyze high-dimensional datasets (behavioral, physiological, neuroimaging) Publish in leading international journals and present
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methodological approaches Proficient in, or willing to learn, programming languages (e.g. MATLAB, Python, R) Experience with one or more of the following is an asset: LCA tools, computational design, structural
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automation, data science, python. The ability to collaborate in a multidisciplinary research environment is essential. Personal initiative, ability to work systematically, reliability, responsibility, teamwork
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analysis, and experimental techniques Background in condensed matter physics or materials science Programming skills (C++, Python, ROOT) are a strong asset Good command of English (spoken and written
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techniques and the physical principles behind them Interest in scientific programming using Python Excellent communication skills and ability to integrate easily into interdisciplinary research team Additional
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with data analysis/modelling and programming (R or Python). Advantageous: geostatistics, digital soil mapping, remote sensing, GIS, big data or cloud tools. Proactive working style, strong communication
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- or nanoplastics, online or offline ice nucleation experiments. A good knowledge of programming languages such as Python, R, MATLAB or IGOR is expected. Excellent English skills, both in verbal and written
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well as programming skills (Python required; experience with seismic data processing is advantageous) Initial experience seismic data analysis and/or wave propagation modelling is an asset Willingness to participate in
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programming (R or Python). Advantageous: geostatistics, digital soil mapping, remote sensing, GIS, big data or cloud tools. Proactive working style, strong communication skills, and excellent English. Relevant
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Programming skills (commonly C++, Python, or similar languages used in HEP frameworks), Monte Carlo simulation methods and data analysis techniques Interest in connecting ideas and people across disciplines