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-time data into WRF-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus
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Bachelor’s degree in physics, computer science, computational biology, or similar fields. The applicant is expected to have demonstrated experience working with state-of-the-art deep learning approaches
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platforms geospatial data analysis and use of GIS software (e.g. QGIS) and cloud-based geospatial analysis platforms such as Google Earth Engine statistical modelling, machine learning, cloud/high-performance
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