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to research and development projects with a focus on modeling and interpreting contaminant transport in the subsurface. Your focus will be on developing, testing and applying numerical models to investigate and
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, or a related field with a focus on groundwater or hydrological modelling Documented experience in numerical or data-driven groundwater modelling (e.g., MODFLOW) Proficiency in handling geospatial and
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, fluid mechanics, solid mechanics, materials science including phase changes, numerical mathematics and data analytics based on statistics and/or machine learning. Each of the postdoc positions will be
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which
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/or (feminist) new materialism will be considered a strength. Experience with qualitative or mixed methods studies of self-tracking technologies and/or practices is also an advantage. The candidate will
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Setup and maintenance of the developed code Integration and development of AI methods in simulation and real systems Profile and requirements The candidates will participate in SDU Robotics’ comprehensive