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statistical analysis and mathematical modelling tools Excellent knowledge of programming languages such as R, Python, etc. Familiarity with AI algorithms and machine learning Excellent written and oral
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of their class with respect to academic credentials. Required: A general physics background on the master-level (MSc or equivalent) including statistical physics, hydrodynamics and soft condensed matter Foreign
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statistical physics and hydrodynamics. Doctoral dissertation must be submitted for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defense are eligible
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or equivalent) including statistical physics, hydrodynamics and soft condensed matter Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system Experience
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to develop implementation measures as part of the fellowship. The fellow is also expected to develop strong skills in advanced statistical methods and finalize three articles within the project period
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groundwater data and statistical/physically-based modelling background to join our team. The postdoc will analyse groundwater level observations and related climate and site-specific data to assess
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following areas: stochastic analysis, stochastic (partial) differential equations, numerical methods in stochastics, probability and mathematical statistics. Candidates without a Master’s degree have until
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statistics, high performance programming, and modeling of Galactic and Interplanetary Dust emission.The successful candidate will work with both newly obtained and archival data at both the map level and at
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the field. The fellow is expected to develop implementation measures as part of the fellowship. The fellow is also expected to develop strong skills in advanced statistical methods and finalize three articles
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covering a wide spectrum of subjects within mathematics, mechanics and statistics. The research is on theory, methods and applications. The areas represented include: fluid mechanics, biomechanics