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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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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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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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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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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
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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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related field Strong Python programming skills and experience with PyTorch or TensorFlow Interest in multimodal data, time-series analysis, or NLP Excellent English; German or French is an asset
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biochemical models, data assimilation, spatial analysis and GIS approaches. • Programing skills (e.g. R or Python) for data manipulation and visualisation, and to perform statistical analysis (e.g. mixed models
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, Statistics or a related field and are motivated to apply advanced analytics to real-world digital health challenges. You have strong foundations in signal processing and are confident working in Python