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use the designed algorithm in practice, we will evaluate how physical constraints, such as payload size, weight, and power supply, and techno-economic tradeoffs affect the optimal HAPS system designs
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Dynamics (SINDy) algorithm applied to numerical and experimental data. You will work closely with the Chemistry group of Prof Anthony Kucernak and the Mechanical Engineering group of Dr Ludovic Renson
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extend a machine-learning inversion algorithm and micromagnetic CRM database to interacting particle assemblages, and contribute to a user-friendly, open-access ChemPI web app. In the final phase you
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author on a novel learning algorithm. Published experience across nanomagnetic, nonlinear nanophotonic, and/or nanoelectronic hardware. Hands-on experience with physical Kolmogorov-Arnold networks and
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data (16S rRNA, metagenomics, or metatranscriptomics) in environmental or biological systems. Computational Modelling: Proven experience in computational modelling, algorithm development, or numerical
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through GPU-accelerated computing, programme-level algorithm differentiation, and advanced software methods for collective operations over large parameter spaces. Outcomes will be embedded in an