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the globe, along with the properties that they carry. However, these currents are profoundly under-sampled by observations and poorly represented in models. One global hotspot of submesoscale ocean
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. Your job In this PhD position, you will conduct idealised experiments with an atmospheric model (OpenIFS), using concepts from the mathematical field of periodically forced dynamical systems. You will
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. However, current estimates of methane emissions from inland waters to the atmosphere are highly uncertain because of limitations in long-term observational data and modelling methodology. In this four-year
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combination with multi-fidelity response models. The multi-fidelity models may include combinations of physics-based response models, Artificial Intelligence (AI) models and probabilistic methods. Your
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the published system-wide salary at the designated rank and step, are offered when necessary to meet competitive conditions. A reasonable estimate for the annual salary for a full-time position is $93,400
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simulations of Jakobshavn Isbræ and NEGIS using the open-source Ice Sheet and Sea Level Model (ISSM). The candidate is expected to perform original research that aims at improving our understanding of past
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) based on different climate scenarios. You will perform the model runs, analyse the results, and compare them to firn properties estimated from (airborne) radar observations and weather station
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communication for global ocean environments: Deep learning models perform robustly on certain environments since they are developed by data in low signal-to-noise ratio. To develop more robust models, we will
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the Western Baltic Sea. The PhD Scholarship includes before-after control-impact (BACI) studies as well as underwater footage to determine fish abundance (MaxN) and biodiversity of mobile fauna (e.g. shore crab
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the seasonality of that precipitation. Past warm climates such as the Eocene provide natural experiments to test model performance in projecting non-analogue future global and regional hydrology and dependence