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quantum chemistry (QM), machine learning (ML), and high-throughput experimentation (HTE). The objective is to develop a data-driven framework that enhances the efficiency and effectiveness of catalyst
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memories) addressing the challenges of scalability, stability and integration of quantum computing. You will have access to our world-class facilities at the Electronics and Nanoscale Engineering Division
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2D materials, searching for exotic quantum functionalities to form new sustainable electronics and new types of computing. Tuning nanostructures of these materials with extreme pressure will unlock
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machine learning algorithms and to assess when AI predictions are likely to be correct and when, for example, first principles quantum chemical calculations might be helpful. Predicting chemical reactivity
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machine learning algorithms and to assess when AI predictions are likely to be correct and when, for example, first principles quantum chemical calculations might be helpful. Predicting chemical reactivity
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. The impact of the research will lead to new types of quantum computers, new lasers increasing the speed of the internet, electronics for manufacturing, and new sensing technologies for monitoring climate
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and spatial resolution, to make a leap in this field. The PhD research programme will squarely address these challenges. The PhD candidate should have completed (or about to complete
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PhD Studentship: Quantum-Uplifted Advanced Resilient Topology Optimisation for Net-Zero Electricity Networks Award Summary 100% fees covered, and a minimum tax-free annual living allowance
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of realising an optical-pump TeraHertz-probe polarisation-resolved near-field microscope, this PhD research programme will look at combining spintronic THz emitters and near-field photoconductive probes. The PhD
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as ligands. The fundamental science behind the selective enrichment of lithium-6 by solvent extraction is poorly understood. This project will combine molecular quantum mechanics and molecular dynamics