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-cases of classical supercomputers, the development of quantum CFD algorithms will be of widespread benefit upon the arrival of fault-tolerant quantum computing. This project involves the adaptation
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. The broad aim of the PhD research is to train the student with skills to investigate self-assemblies of lipids and biocides (cationic surfactants) and their cross-assembly processes, and identify how
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manufacturing (3D printing) techniques. The purpose of the studentship is to develop a next-generation in vitro model of aged human skin to evaluate the cytocompatibility of materials used in maxillofacial
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interference, while ensuring energy-efficient and scalable operation. This PhD project will focus on developing machine learning algorithms to enable robust channel estimation, intelligent user association
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learning algorithm to develop an ability to choose what main data pattern/structure to preserve? This PhD project will approach this question by developing modelling strategies and pipelines to enable human
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, the successful candidate will develop parametric microscale lattice structures capable of a wide range of mechanical properties (including auxetic and non-linear elastic response). Artificial Neural Networks (ANNs
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(ESBMC, CBMC, Z3, or similar) – either academic or practical. • Programming proficiency in C/C++, Python, and familiarity with software verification tool development. • Understanding of ML/NLP fundamentals
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protein synthesis platforms. These modified proteins will be studied for their biophysical properties, reactivity, and potential applications across chemical biology, therapeutic development, and
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High Voltage DC transmission (HVDC). So far, such links have predominantly been directly from a wind farm to shore (point-to-point). However, proposals are developing for multi-terminal grids
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ligands holds vast potential for developing a new class of main group catalysts with the potential to rival or even exceed the performance of traditional transition metal systems in selected transformations