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applicant must hold a PhD/DPhil in a relevant subject. They must have peer-reviewed publications using data science approaches, for example, genetic analysis, including Mendelian randomisation and genetic co
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attached to the project. The successful applicant must hold a PhD/DPhil in a relevant subject. They must have peer-reviewed publications using data science approaches, for example, genetic analysis
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. The post-holder will have the opportunity to teach. Applicants should hold PhD in Astrophysics or a related field. A strong background in Radio interferometry observation and sufficient specialist knowledge
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. The post-holder will have the opportunity to teach. Applicants should hold PhD in Astrophysics or a related field. A strong background in Radio interferometry observation and sufficient specialist knowledge
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-edge machine learning techniques will be used, including Large Language Models (LLMs). About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the
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research into planet formation/protoplanetary discs or the ISM/star formation and may also have some experience in statistical methods and/or machine learning. Dr Winter and QMUL are committed to improving
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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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analysis of data from a Nipah virus vaccine trial, using machine learning and statistical tools to identify immune response markers for future trials. You will be responsible for developing new and adapting
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independent study and training courses. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics, statistics, physics, engineering, data science or a related discipline, and have
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to science. This is the first large-scale study of its kind, and your results will establish a legacy of scientists working with funding councils to defend their research. Cutting-edge machine learning