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). The post is funded by NIHR and is fixed-term for 24 months, with a possible extension. This project is about creating novel AI models to predict patient outcomes following acceptance or refusal of an offer
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of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain
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tomato and pepper as model systems. Work in Oxford will build on our extensive experience in studying bacterial virulence mechanisms and the role of the plant microenvironment in disease development
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into the ethical governance of Large Language Models (LLMs), as part of the prestigious Divirsibus Vis Plurima Solvo project. The position is full-time and fixed term for 41 months or to the funding end date of 30
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of advanced X-ray methods to explore chemical, crystallographic and morphological changes that drive battery performance loss. You should possess a doctorate in a relevant engineering or physical science
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challenge. We seek a senior computational biologist to apply these extensive in-house datasets toward the development of novel, domain-tailored machine-learning models and analytical methods. You will explore
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scientific oversight from Oxford Principal Investigators and GSK scientists, the centre will initially focus on some of the following thematic areas: • Decision analysis under model misspecification
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original research on the grid integration of second life battery storage systems. The research will bring together second-life battery modelling, power system optimisation and technoeconomic evaluation
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experience in working with human neuronal cell lines that provide models of understanding the biology of protein aggregation and its phenotypes. About you Applicants must hold a PhD in Chemistry or a relevant
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, biochemistry, cell-based and model organism. You will be expected to manage your own academic research and administrative activities. This involves small scale project management, to co-ordinate multiple aspects