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under a hybrid working model. While flexibility is supported, the post-holder will be expected to work onsite when required to meet the operational needs of the department. It is a fixed term contract
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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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Associate Professors or Professors of Computer Science to start on 1 September 2026. Each post is associated with a Non Tutorial Fellowship at Kellogg College. Three of the positions are for research within
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collaboration with the research team. Additionally, you will provide guidance to laboratory and biostatistical staff, assisting with project-related tasks as needed. You must hold a PhD either in Bioinformatics
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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form, how it is generated and how it evolves. In particular we focus on the evolution and evolvability of vertebral counts, and we use various species of Lake Malawi cichlids as our model organism
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South, the successful candidate will draw on existing datasets and behavioural science frameworks to create a large language model (LLM)-powered tool that supports key behaviour change techniques central
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database that works with national agencies, other Universities, and collaborators across the country to deliver world class research and surveillance insights. The successful applicant will help maintain and
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and actively contribute to the wider academic environment of the group. It is essential that you hold a PhD/DPhil (or close to completion) in immunology or a related biomedical discipline and have
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Demographic and Health Surveys, the Generations and Gender Survey, the International Public Use Microdata Series, and the Human Fertility Database, among others, and linking these data with other databases