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multiple ship classes and shore power applications. The project seeks to deliver industry-relevant modelling toolkits that enable optimal design and operation of greener vessels, backed by real-world
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to have published in leading machine learning conferences or similar venues. One or two PDRAs will be recruited to work within one of, or across, the four research themes: Learning with Structured
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multiple ship classes and shore power applications. The project seeks to deliver industry-relevant modelling toolkits that enable optimal design and operation of greener vessels, backed by real-world
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Assistant (RA) or a Postdoctoral Research Associate (PDRA). The appointed candidates will support advanced research initiatives focusing on systems design, distributed systems, and algorithmic optimization
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of accidentals and low-energy signals, characterize background populations, improve event reconstruction, and understand detector effects. They will contribute to LZ operations and performance optimization
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of accidentals and low-energy signals, characterize background populations, improve event reconstruction, and understand detector effects. They will contribute to LZ operations and performance optimization
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Hours of work: Full-time Tenure: Available from 1 October 2026 until 30 September 2028 Hybrid Working: Hybrid Working - minimum requirement of 40% on Campus, with 60% considered desirable where
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Hours of work: Full-time Tenure: Available from 1st October 2026 until 30th September 2028 Hybrid Working: Hybrid Working - minimum requirement of 40% on Campus, with 60% considered desirable
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. This role may focus on simulations and signal models, dataset curation and statistical package development in support of such searches. They will contribute to LZ operations and performance optimization
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detector effects. They will contribute to LZ operations and performance optimization. This will involve adapting existing and developing new scientific techniques; contributing ideas for new research