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Field
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of barrier winds off East Greenland using new wintertime observations from a research cruise. Carry out numerical weather prediction simulations of barrier wind case studies with the observed sea-ice
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knowledge gaps. The project involves both linear and nonlinear dynamics modelling and analysis, as well as experimental testing. An equivalent test structure will first be constructed in the vibration
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determining the drivers of these changes from the oceanographic data and model experiments as well as satellite and reanalysis products. Training: You will develop skills in chemical analysis, data processing
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to learn laboratory methods for analysis of relevant BGC parameters. Training: You will be based in the Polar Oceans Team at British Antarctic Survey, a highly active research team focused on both
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FRCs. You will receive training in instrumental techniques, including stable isotope analysis using specialised equipment within the UEA Science Analytical Facilities, as well as high-throughput
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-equilibrium conditions. The project is a UKRI/NSF collaboration with Virginia Tech, and the use of direct numerical simulation, modelling and analysis will be complemented with experimental data from
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on the topic (2,4). Training and Development Training will maximise future employability in academia and industry: Programming and geospatial data analysis using Python/R. Machine/deep learning techniques
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of machine learning, numerical analysis, optimisation, or related fields. Funding notes: Funding is available through the School of Mathematics for a suitably strong candidate. The scholarship will cover
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the pathways and fate of the Atlantic Water that enters the Arctic Ocean through virtual particle tracking and heat budget analysis. Study how sea ice losses influence ocean-atmosphere-ice exchanges
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programming and modelling frameworks (JuMP, Pyomo, Yalmip, GAMS, etc) Experience with unbalanced distribution system analysis tools (e.g., OpenDSS, Cyme, Gridlab-D, PowerModelsDistribution.jl) Experience