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on evaluating the abilities of large language models (LLMs) of replicating results from the arXiv.org repository across computational sciences and engineering. You should have a PhD/DPhil (or be near completion
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and organise data from public sources, surveys, and institutional datasets, in both Chinese and English language, conduct advanced text analysis using NLP techniques, and apply and fine-tune LLMs
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to the 4th February 2026. You will be investigating the safety and security implications of large language model (LLM) agents, particularly those capable of interacting with operating systems and external APIs
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-workers. Excellent oral and written communication skills, including proven ability to write in English at a suitable standard You will experience of flow cytometry and experience with tissue culture
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R
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surveys, early universe and gravitational physics. Good programming experience, an enthusiasm for coding and data analysis, and the ability to work in a large collaboration, are particularly relevant
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coding experience (both Python and C/C++), and a record of working in a Linux environment and related scripting languages. What we offer At the university of Oxford your happiness and wellbeing at work is
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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ideas for new research projects and research income generation. You will also have excellent interpersonal and communication skills, with excellent written and spoken English and Japanese. Previous
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concept of agents has come to the fore again, prompted by the rise of Large Language Models (LLMs) – put crudely, the idea is to use LLMs, in the sense of being powerful general purpose intelligent systems