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of micropollutants Good basics in hydrological and substance flow modelling Experience in statistical data evaluation and programming skills (R, Python, etc.) Language skills Fluency in English and French or German
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sustainability, environmental systems, and spatial data Skills in the following areas: Data analysis and programming, e.g. Python, R GIS and spatial analysis Data visualisation Language Requirements: Applicants
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, misinformation intervention, and computational social science Solid programming skills, e.g., Python, machine learning frameworks, data analysis tools Experience with social media research or large language models
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, including, but not restricted to, geometry or shape optimization, parameter optimization, or multi-objective optimization. · Strong programming skills (e.g. Python, C/C++, R or similar) and experience
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, Engineering or Chemistry Familiarity with areas such as design-of-experiments, soft matter physics, experience in programming (e.g. Python) Experience in X-Ray scattering, rheology or thermal analysis are a
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) Proficiency in scientific programming using Python, with experience in Matlab and/or R considered an asset. Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX. Experience in
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, problem solver, and programming skills for Python and Matlab are preferred Experience in similar environments with industrial collaborations or public-funded research projects is highly desirable Fluency in
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flows, diffusion models). Hands-on experience in multi- and hyperspectral image processing (e.g., IDL/ENVI) and RTM inversion (e.g., ARTMO) Proficiency in scientific programming using Python, with
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optimization, parameter optimization, or multi-objective optimization. · Strong programming skills (e.g. Python, C/C++, R or similar) and experience using scientific computing and optimization libraries
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
demonstrated proficiency with computer coding, such as Python, MATLAB, R, and expertise in statistical modelling. · Experience in designing, planning, and conducting experimental procedures, including