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for a technician who will help with the quantitative analysis of a European travel survey and apply data science methodologies to predict travel behaviour in European cities as part of the EC funded
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vegetation model. The new EEO-based vegetation model should then also be used to predict future transitions and biome shifts to ultimately answer the question to what extent C4 grasslands, savannahs and their
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, as well as from industry. The successful candidate will work in the established collaboration between DSB and ICGI to develop multimodal deep learning models for predicting prostate cancer
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or biases in data collection, storage, and processing pipelines. Additionally, the candidate will develop AI models that can adapt to dynamic and evolving data environments, incorporating mechanisms
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so that we can improve the prediction, diagnosis, prevention and treatment of common diseases such as Alzheimer?s, cancer and cardiovascular disease. We take a computational approach focused on
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environmental science is of supreme importance. Students entering the science classroom bring well-developed intuitive frameworks that help them understand, explain, and predict the world around them. These
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to pre-train a common GNN backbone model capable of predicting electronic, structural, and thermal quantities while leveraging underlying symmetries for computational efficiency. There will be a
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predicting pollutant dispersion in complex environments like industrial sites remains difficult due to fluctuating wind conditions and obstacles. This PhD project offers a unique opportunity to develop
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at two levels: SAACD Component: This is a UAV made up of hardware and software sub-systems, capable of observing, predicting, deciding and reconfiguring itself to fulfil its mission (e.g. surveillance
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of switchable RNA nanostructures. Develop databases for RNA modules for automated building of atomistic models. Develop multistate sequence design algorithm for rational design of RNA switches. Develop database