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explore current techniques such as fine-tuning, model alignment, prompt engineering and Retrieval Augmented Generation (RAG) to improve reliability of generated recommendations for two cases of chronic
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scenarios when a solver needs to be used "incrementally" when dealing with a sequence of "similar" problem instances. This project is devoted to tackling the challenges arising in the incremental use of a
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innovating interesting models to address different aspects of this problem (eg [1,2]). [1] Sequence to Sequence Mixture Model for Diverse Machine Translation Xuanli He, Gholamreza Haffari, Mohammad Norouzi In
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an original short research proposal that responds to one or more of the broader project’s objectives, aligned with the candidate’s areas of interest and/or expertise. We do not expect the successful candidate
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common purpose. Underpinning your approach are your intellectual capacity and creative growth mindset, stamina and agility to manage multiple priorities. Your experience may span higher education or other
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optimisation team while liaising with industry partners to align research goals with their priorities. There will also be opportunities to publish findings in leading optimisation venues. Key Responsibilities
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analyse and harmonise large-scale claims, service and payment data across multiple jurisdictions—delivering insights that can influence national injury prevention and health policy. You’ll be part of
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search is guided simultaneously by multiple contrasting objectives: maximising the QA resources on software modules that are risky, severe, and affect a large number of end-users, while minimising the cost
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working on harnessing new technologies such as next-generation sequencing and artificial intelligence to improve the diagnosis, treatment and prevention of AMR infections. The specific aims of this project
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environmental stewardship in Antarctica and the Southern Ocean. The ideal candidate will have extensive experience in developing complex proposals for large-scale, multimillion-dollar projects involving multiple