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, deployment and evolution of AI agents. By establishing foundations for trustworthy agent engineering, FRAME will enable productivity, adaptability, self-improvement, reliability and foster large-scale adoption
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for better training and novel network designs. Low Effective-dimensional Learning Models. We will extend foundational theory of how large ML systems can be regularised to have dramatically fewer trainable
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/opportunity-spaces/resilient-climate-and-ecosystems/accelerated-adaptation for more information on ARIA and this programme). The project is a collaboration between groups at the Universities of York and Exeter
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work to generate high fidelity models of ice crystal icing shedding, verifying tools using a wealth of unique experimental validation data generated by researchers at the Oxford Thermofluids Institute
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. The research will be carried out at the Department of Information and Communications Engineering, DICE, at Aalto University, Finland. The project environment offers excellent infrastructure for deep learning
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such as breakwaters by using computational tools developed in our research group. These tools are based on discrete element method and they have bee validated against experimental data. You will start your
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optimization of large language models (LLMs) and related architectures for generative tasks, continuous learning, indexing or retrieval, support of retrieval augmented generation over many data points from long
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demonstrate equivalent research experience and qualifications. Experience in both wet-lab and dry-lab research is beneficial. You must have expertise in analysis of large-scale genomic data and confidence in R
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community. The research will be carried out at the Department of Information and Communications Engineering, DICE, at Aalto University, Finland. The project environment offers excellent infrastructure
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, bioelectrical signalling and fibrotic cell-state transition. More information on the project can be found here: https://marcfernandezyague.com The successful candidate will conduct experiments at the Queen Mary