This is an exciting opportunity to join an interdisciplinary research group and contribute to, and lead, innovative and high-impact research in population health and global health. The overall theme of the research is analysing the trends in different measures of population health. The work is at the cutting edge of global health science and data analytics and arises from collaborative research with the World Health Organization and with a network of scientists from most of the world’s countries, which will give the work significant scientific and policy impact and visibility.
You will be based in the Global Environmental Health Research Group (www.globalenvhealth.org) at Imperial School of Public Health, which is internationally renowned for data-driven research on population health and global health.
You must have exceptional analytical and critical thinking about scientific problems, deep knowledge and intuition of quantitative methods, motivation for problem solving; experience with large heterogenous datasets, ability to efficiently manage large quantities of data, excellent coding skills in R or related programming languages, strong communication capabilities, aptitude for interdisciplinary research and teamwork, and ability to work and learn independently.
Duties and responsibilities
Potential areas of work include: clustering and trends in multiple health conditions; detecting periods of acceleration or stagnation in health improvement; health forecasting; health inequalities
Contribute to scientific studies, including data collation/management, development and implementation of methods, analysis and interpretation of results
Maintain accurate and complete records of all analyses, and their methods and findings
Contribute to publications to refereed journals
Present research findings at academic conferences and to non-technical audiences
Contribute to reports for submission to research sponsors
Attend research group meetings and other relevant meetings
Undertake any necessary training and/or development
A strong undergraduate degree or MSc in mathematics/applied mathematics, physics, applied statistics, data science, engineering, epidemiology or a related subject
Experience in application of quantitative/statistical methods
Research experience in a quantitative discipline or using advanced quantitative methods
Experience in exploring, managing and preparing large, multi-dimensional and heterogeneous datasets
Experience of using and programming in R or related programming languages
Knowledge of quantitative methods from (applied) mathematics, statistics, econometrics, machine learning, and ideally a combination
Knowledge of complex data and databases
Knowledge of R or related languages
Programming in R or related programming languages
Excellent written and oral communication skills and the ability to write clearly and succinctly
Ability to effectively communicate/work with diverse group of collaborators
Ability to write research papers and reports
An interest and willingness to learn new skills quickly
Superior ability to understand and effectively present complex concepts and data, especially for scientific data
A meticulous approach and attention to detail
Superior critical thinking
Ability to prioritise tasks and organise work effectively to meet deadlines, including in the presence of competing demands on time
Ability to work well independently as well as part of a team
Ability to work with a minimum of supervision
Excellent organisational skills
For more information and to apply, click 'Apply Here'.