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identified by, a set of parameters. Such methods are a popular choice in quantum dynamics, where the wavefunctions of many-body systems are approximated by multiple Gaussians. The methodology of interest
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: We welcome applicants from Physics, Materials Science, Chemistry, or related disciplines who have at least an Upper Second-Class Honours Degree or equivalent. A background including courses in quantum
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for exploring phonons and emergent phenomena in future spintronic and quantum technologies. The successful candidate will benefit from strong national and international collaborations throughout the project
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, you will develop low-cost quantum mechanical approaches to modelling the effect of non-covalent interactions on bond decomposition (pubs.rsc.org/en/content/articlelanding/2025/cp/d5cp00852b ), and the
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(or equivalent) in Physics, Mathematics, or a closely related discipline. A background in quantum mechanics is essential. Experience in nuclear physics, statistical methods, or scientific programming
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generative AI framework that utilizes machine learning predictions and quantum chemistry simulations to design stable, synthesizable, high-performance molecules. The framework will integrate multi-objective
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, including in liquids. Combining quantum mechanics and atomic simulation with AI-driven sampling techniques, you will determine terahertz and Raman spectrograms to directly compare to measurements obtained in
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, FCVD creates a liquid-like layer that fills narrow trenches on substrates before solidifying into films. We will model this across multiple scales, from atoms to fluid flow, using quantum chemistry
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-assisted discovery and development of semiconductor materials and devices. This exciting new field will lead to new types of quantum computers, new lasers increasing the speed of the internet, electronics