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a hip or knee replacement. The project team, led by Alex Bottle, professor of medical statistics, is multidisciplinary, including surgeons, allied health professionals, and social scientists. You will
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analysis in biomedical data, in affiliation to the Artificial Intelligence Research Centre . The successful candidate will develop statistical and machine learning techniques to analyse biomedical data. High
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)) models are used at all stages of pre-clinical and clinical development, but they are based on mathematical and statistical principles dating from the 1970s. Developing these pharmacometric models remains a
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they are based on mathematical and statistical principles dating from the 1970s. Developing these pharmacometric models remains a laborious task where highly qualified staff spend large amounts of time. Aims
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and Surveillance group. Within a week of working here, your day could look like this: you will be applying your epidemiological, statistical and leadership expertise to a range of studies to develop and
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will be to: Research statistical methods and industrial production theory to develop a generic approach to the problem. Compile a comprehensive list of manufacturing parameters, material properties and
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Attend UCL courses and training (e.g. in research study design, good clinical practice, medical statistics, time management, paper writing). Literature research Manuscript writing for submission to peer
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costs of their project. We will support two students, one in the area of health data science/epidemiology/statistics and the other specialising in applied machine learning and informatics. The closing
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health (3) Support and training The doctoral student will be supported by a team with expertise in plant biology, soil health, next generation sequencing and statistics and they will work within an active
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distinction is desirable, but not essential. Strong statistical skills, and experience with designing and implementing experiments with human participants, are useful. Applicants will need to submit a CV, a