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actors. The developed algorithms will be validated using simulation testbeds and simple hardware-in-the-loop microgrid setups with battery storage. Overall, this research will advance the state of the art
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are poised to re-define our future mobility. However, full autonomy is not possible without all-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms
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into smaller, faster, more energy efficient and cost-effective hardware compared to the current state-of-the-art. The project will align the in-house algorithm-to-hardware development of the Micro-Systems
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compared to the current state-of-the-art. The project will align the in-house algorithm-to-hardware development of the Micro-Systems Research Group at Newcastle University with next-generation Field
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-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms, using signal processing/machine learning techniques, to realise all-weather perception in
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patterns across multiple annotation types. The core aim is to generate new scientific insight by associating LCRs with their functions through a combination of expert curation and modern machine learning
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Applying machine learning-guided directed evolution to improve multiple enzyme properties Upscaling selected biotransformation reactions in collaboration with academic partners Responsibilities and
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generation sequencing Applying machine learning-guided directed evolution to improve multiple enzyme properties Upscaling selected biotransformation reactions in collaboration with academic partners
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candidate will contribute to: Developing supervised deep learning algorithms for 3D point clouds Developing self-supervised deep learning algorithms for 3Dpoint clouds Expand for a wider variety of downstream
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network aims to deliver fiber-optic quality experiences over wireless links by building the theoretical, algorithmic, and architectural foundations of THz systems. It introduces ultra-MIMO (multiple-input