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. For this PhD position you will work on modelling the processes and feedbacks that couple the AMOC and polar ice sheets, with particular focus on sea ice and (North Atlantic) deep-water formation regions such as
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potential large-scale climate repercussions. Even more so since the AMOC brings CO2 from the surface to the deep ocean during deepwater formation (physical pump), and variations in the AMOC strength will
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four-year PhD position in Deep Learning for Metocean data (surface waves and ocean parameters) at the Division for Oceanography and Maritime Meteorology at The Norwegian Meteorological Institute (MET
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relevant experience in the development and deployment of machine/deep learning models as well as the use of remote sensing data You must have relevant experience in the development of hydrodynamic and water
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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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Characterization Techniques Study the advanced electrochemical characterization methods. Gain deep insights into the reaction models associated with PCFCs. 3) Understanding of Electrocatalytic Performance and
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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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exchanged between land, ocean and atmosphere through processes known as global biogeochemical cycles. Research activities in the IMPRS-gBGC aim at a fundamental understanding of these cycles, how