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on the sustainable use of the marine environment through ecosystem-based management and marine spatial planning. Developing ways to make this advice climate-proof and identify climate-ready solutions. Contributing
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simulation concepts with experience in wildfire modeling and loss assessment and regional planning of communities at the wildland-urban interface (WUI). Successful candidates will contribute to the development
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. Developing relevant modelling tools to support comprehensive analyses of livestock systems. Assessing environmental impacts of current livestock production systems and evaluating potential outcomes from
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Centre of Excellence “Temporal and Spatial Dynamics of Forest-Related Chemical Interactions in the Anthropocene.” The doctoral researcher’s duties include studying the effects of climate change, air
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various data types such as whole-genome sequencing (WGS), whole-exome sequencing (WES), RNA sequencing, spatial data, etc, and will also include rich clinical annotation to explore the clinical implications
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or computational methods (e.g., remote sensing, spatial analysis, systems or integrated assessment modelling) applied to sustainability. Candidates from other methodological areas with clear environmental and
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Results: Ability to assess the influence of the engine plume on the release of emissions into different atmospheric layers. Numerical model to describe the temporal and spatial dispersion behaviour
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the Telemark Canal , focusing on digital twin-based preparedness modelling for cultural heritage infrastructure. The primary objective of the position is to complete a doctoral education leading to a PhD degree
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addition to an extensive observational programme, the project will bring together a suite of existing models, ranging from spatially explicit lower trophic level models through fish population models to fisheries management
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interdisciplinary collaboration, in addition to their own specialty. Skills and knowledge related to data handling, such as the acquisition, analysis, and modeling of observational data, are highly desirable. 2