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health. You will develop and apply cutting-edge machine-learning techniques to identify the most informative indicators of ecosystem change and use them to build dynamic Bayesian network (DBN) ecosystem
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ability to evaluate fossil fuel CO2 (ffCO2) emissions is currently limited. ‘Bottom-up’ emissions estimates, based on inventory-style accounting and mobile tracking data, can differ significantly from each
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ecology and oceanography, the project will leverage large existing datasets on (i) the movement of migratory seabirds throughout their annual cycle, available via BirdLife’s Seabird Tracking Database (STD
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results align with the abundance and expression of diatom ppRHO genes in the surface oceans. Research methodology Objective 1: Identify the subcellular localisation of two different ppRHOs isolated from
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melt and warming raise concerns on how these climate-driven changes will impact future CO2 uptake by these polar waters. Project objectives: The project objectives are to extend the Rothera carbonate
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objectives of this project are to 1) differentiate between magmatic and post-emplacement microstructure, and 2) identify the effect of deformation on the geochemistry of the main rock-forming minerals
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OBJECTIVES � Primary focus areas, with potential to tailor according to your interests.� Assess how nesting environment and microbial supplementation influence microbiome colonisation.� Determine microbiome
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spectral sensitivities, varying daylight illumination spectrum and wide range of relevant material reflectance spectra. Objectives Develop a multispectral imaging dataset of marine litter materials by
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an exceptionally powerful database. The following novel objectives can then be tackled, with components being developed and prioritised according to your interests: 1) Test the relationship between mutation-scores
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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