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. Experience Machine learning (ML) and/or optimization for communication systems Development, implementation and verification of ML algorithms in code Algorithm development and performance analysis of
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. This position at Imperial will lead the experimental development and application of ChemPI under the guidance of Adrian Muxworthy and Dominik Weiss, whilst the numerical and micromagnetic modelling
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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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will focus on development methods for aircraft design in dynamic environments. Computational strategies for aircraft design optimisation are currently based on static (or static equivalent) conditions