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of Immunity – Artificial Intelligence (CoI-AI) Programme, a pioneering initiative that integrates controlled human infection models, advanced immunology, and AI-driven analytics to accelerate vaccine discovery
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candidate will conduct hands-on empirical research that embraces both experiments and modelling and be responsible for three stands of research (i) using industrial data (and working with industry) to model
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academic environment. About the role: The post is offered as a full-time, fixed-term contract for an initial period of one year. The successful candidate will develop and implement novel analytical pipelines
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, organising and analysing data, supporting thematic and narrative analysis of legal judgments and statutory reports, contributing to the development of an interdisciplinary analytical framework, and assisting
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Are you passionate about using geospatial data and place-based analytics to address mental health inequalities in rural and coastal communities? The University of Lincoln is seeking an ambitious
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analytical techniques, opportunities to supervise students, and involvement in manuscript preparation and future grant applications. It is essential that you hold (or are close to completion) a PhD in cell
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-learning models based on first-principles data and apply these methods across increasingly complex structures and chemical systems. The role will involve both methodological development (datasets, models
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previously been subject to various analyses. The analytical data is currently preliminary and incomplete. You will work with the unpublished dataset, identify data gaps and to carry out new analytical work
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of Immunity – Artificial Intelligence (CoI-AI) Programme, a pioneering initiative that integrates controlled human infection models, advanced immunology, and AI-driven analytics to accelerate vaccine discovery
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are looking for a researcher with a PhD (or near completion) in engineering, data science, computational social science or a related discipline, with experience in data analytics, NLP or machine learning. You