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(Denmark) places the student in world-leading centres for routine health data analysis, with extensive experience in implementing novel clinical epidemiological methods to study disease occurrence, aetiology
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Aarhus University (Denmark) places the student in world-leading centres for routine health data analysis, with extensive experience in implementing novel clinical epidemiological methods to study disease
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Centre for Eye Health (ICEH) at LSHTM and multiple global stakeholders. The candidate must have a relevant first degree in the field of global public health, ophthalmology, epidemiology or other relevant
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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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regression analyses is important. It is essential that you have an MSc (Research Assistant) / PhD (Research Associate) in epidemiology, statistics, health economics or related quantitative field or a closely
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countries to create a strong global research community with interests in public health, health inequalities, maternal and child health, health informatics, epidemiology, chronic and infectious diseases
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. Eligibility Criteria A 2:1 honours degree, or international equivalent, in a relevant subject (e.g. health sciences, epidemiology, statistics, psychology, medicine, pharmacy, nursing, midwifery, allied health
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statistical modelling, epidemiology, population data science and health technology assessment, with the opportunity for their research to directly inform healthcare policy and practice. The successful student
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strategies of patient care. To do this, advanced molecular, sequencing and bioinformatic tools will be utilised alongside clinical data that will provide a link between the genomic and epidemiological data
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outcome could focus on its broad conceptualisation or on specific sub-domains. This could focus on generating epidemiological evidence on health impacts, using secondary data sources, including cohorts