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as early indicators of anthropogenic and climate-driven change. However, limited understanding of the processes shaping species’ biogeographic distributions constrains our ability to predict ecological
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Boltzmann method simplifies the numerical treatment of fluid flows by evolving particle distribution functions across straight lines on a computational grid, rather than evolving the trajectories of the flow
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algorithms * Parallel algorithms and distributed computing * Parameterized complexity and structural graph theory * Random structures and randomized algorithms * Sublinear and streaming algorithms
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King's College London Department of Engineering | London, England | United Kingdom | about 11 hours ago
through the EU Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description About the Project This PhD project in fire
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. road, power distribution). This project will develop new insights into what drives flooding and extreme wind to co-occur on timescales from (sub-)daily to seasonal. Our recent work suggests that
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associated with genome dominance. Transposable element distribution and activity will also be analysed using long-read sequencing. This project is primarily computational and offers comprehensive
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technologies (LCTs, such as solar PV, electric vehicles, heat pumps or energy storage) to distribution networks. New active technologies that provide flexibility, such as network operator-owned power electronic
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PhD Studentship: The Role of O-glycosylation of the Stalk Region of the Immunoglobulin Receptor GPVI
to determine their effects on GPVI signalling. In addition, super resolution microscopy will be used to determine how glycosylation effects the distribution of GPVI on the cell membrane. Finally, nanobodies will
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interact without full trust in a centralized party. This research project aims to develop cryptographic solutions and frameworks that secure AI systems, particularly in decentralized and distributed settings
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. The Role This is an exciting opportunity for a highly motivated and skilled Research Associate/Assistant in statistics to join the EPSRC funded project PINCODE: Pooling INference and COmbining Distributions