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model due to the mathematical challenge of solving the multiple partial differential equations simultaneously. With the support of the combined sponsorship from the university and industrial partner
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project TARGET-AI will bring together expertise from multiple research groups to advance the state-of-the-art in combining the most advanced techniques from deep learning/AI with rigorous statistical
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techniques to combine data from multiple sources, integrating both visual and textual information to deepen our understanding of patient health. This studentship offers a unique opportunity to contribute
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neuroimaging techniques. You will conduct both neuroimaging and neural network modelling studies to determine whether and how combining information across multiple sensory modalities (vision and touch) may
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often fail to preserve the fidelity of combined datasets, leading to loss of crucial information. This proposal aligns directly with the CAMS Data Analytics Theme and the Grand Challenge of using machine
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students and senior researchers from multiple disciplines to tackle challenges in sustainable aluminium through AI-driven microstructural analysis. The NEST-WISE project offers a vibrant collaborative
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of the ECHO-EMG research initiative, funded by the Independent Research Fund Denmark (DFF). The project aims to develop a novel system that combines high-density surface electromyography (HD-sEMG) and
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certain class of cyclic aromatic compounds that have been first proposed by Heilbronner in 1954, but still are elusive till date. By combining the expertise of synthesis, matrix isolation, on surface
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Professor that will be capable of contributing to multiple ongoing research projects in the lab. Potential projects include, but are not limited to, oceanographic characterization of deep-water habitats, GIS
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implement innovative solutions to enable seamless operation in connected and autonomous mobility use cases. - Validate research outcomes through a combination of high-fidelity simulations and