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dynamics) processes influencing energetic particle precipitation into the atmosphere statistical methods for handling complex data Experience from data analysis using scientific programming, e.g., Matlab
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PhD: Development and application of Machine Learning for downscaling climate predictions/projections
Mathematics » Statistics Researcher Profile First Stage Researcher (R1) Country Norway Application Deadline 30 Apr 2024 - 23:59 (Europe/Brussels) Type of Contract Temporary Job Status Full-time Hours Per Week
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PhD: Development and application of Machine Learning for downscaling climate predictions/projections
countries. Qualifications and personal qualities Applicants must hold a master's degree or equivalent education in atmospheric sciences, statistics, computer science, applied mathematics or related
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PhD: Development and application of Machine Learning for downscaling climate predictions/projections
centres in Europe with around 200 scientists from 37 countries. Qualifications and personal qualities Applicants must hold a master's degree or equivalent education in atmospheric sciences, statistics
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PhD: Development and application of Machine Learning for downscaling climate predictions/projections
countries. Qualifications and personal qualities Applicants must hold a master's degree or equivalent education in atmospheric sciences, statistics, computer science, applied mathematics or related
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PhD: Development and application of Machine Learning for downscaling climate predictions/projections
centres in Europe with around 200 scientists from 37 countries. Qualifications and personal qualities Applicants must hold a master's degree or equivalent education in atmospheric sciences, statistics
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must hold a master's degree or the equivalent in medicine, health sciences, statistics or equivalent method-oriented subjects, or must have submitted his/her master's thesis for assessment prior
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in machine learning or statistical learning and hands-on experience in data analysis and modelling hands-on knowledge in building and experimenting with sensor-based systems. the candidate should be
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in machine learning or statistical learning and hands-on experience in data analysis and modelling hands-on knowledge in building and experimenting with sensor-based systems. the candidate should be