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/10.1021/acs.jpcb.4c01558 ], but they lack accuracy for predictive modelling. Transferable machine learning potentials, like MACE-OFF [https://doi.org/10.1021/jacs.4c07099 ], effectively achieve quantum
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shift from microwaves to mm-waves (ca. 30 – 300 GHz) or even Terahertz frequencies (ca. 0.3 – 1 THz). Current on-chip interconnect technology relies on printed circuit board (PCB), which is not suitable
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surface roughness, and undergoes absorption and scattering by molecules and suspended particulates in the atmosphere. Any viable mobile radio communications technology at THz frequencies must operate both
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probe may be required for the latter. Subsequently, the PhD student will embark on electromagnetic design of metasurfaces combined with spatially selective defect engineering for the realization
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matrix functions. These computational problems are central to many scientific and engineering applications, including quantum mechanics, materials science, and weather/climate modelling. Numerical methods
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Application deadline: All year round Research theme: Department of Chemical Engineering; research theme: advanced functional materials and analytical science How to apply: https://uom.link/pgr-apply
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research focuses on Materials physics, Quantum technology, Soft & living matter, and Advanced energy solutions. Topics extend from fundamental research to important applications. We educate future
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for Security Operations Centres (SOCs) while pioneering strategies for quantum-era resilience. This project sits at the intersection of Artificial Intelligence, Cybersecurity, and Explainable Computing. It
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approaches for designing new supramolecular materials. Using, for example, a mixture of classical and quantum mechanics simulations, cheminformatics and coarse-grained simulations, we will uncover the design
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platforms, enable light manipulation for next-generation ultrafast applications in spectroscopy, sensing, and telecomms. Ultrafast lasers drive innovations from quantum technology to medical imaging, yet