Research Associate in Statistical Machine Learning and Population Health
Applications are invited for a research associate position in the Department of Mathematics at Imperial College London to work in the area of statistical machine learning with applications in population health. The overall theme of the research is to develop methods in statistical machine learning to study worldwide phenotypes and transitions in multiple health outcomes. The position is funded through an UKRI Medical Research Council grant...
Job listing information
- Reference NAT01306
- Date posted 24 October 2022
- Closing date 23 November 2022
Applications are invited for a research associate position in the Department of Mathematics at Imperial College London to work in the area of statistical machine learning with applications in population health. The overall theme of the research is to develop methods in statistical machine learning to study worldwide phenotypes and transitions in multiple health outcomes.
The position is funded through an UKRI Medical Research Council grant which involves collaborative research among statisticians and health researchers at Imperial College as well as with a network of scientists from most of the world’s countries, which will give the work significant scientific and policy impact and visibility. The post-holder will be based in the vibrant Statistics section of the Department of Mathematics, which is consistently ranked as one of the top in the country for research and has world-class expertise in statistical machine learning, and will collaborate with the Environment and Global Health Research Group (www.globalenvhealth.org) at Imperial School of Public Health.
Duties and responsibilities
The project will involve the development of Bayesian hierarchical models to identify multimorbidity clusters and investigate the variation in both magnitude and characteristics of these clusters across and within regions of the world. The work is at the cutting edge of both statistical machine learning and population health science and the post-holder will be expected to collaborate with population health researchers at Imperial.
The successful candidate will hold a PhD or equivalent level of professional qualifications in statistics, mathematics, computer science or closely related discipline.
- Hold a PhD (or equivalent) in Mathematics, Statistics, Physics, Computer Science or a related subject
- Experience in probabilistic modelling and computational statistics or machine learning methods
- Desire to develop statistical machine learning with applications in population health
- Experience in carrying out research of high quality, independently and in a team, evidenced by publications of high quality
- Experience implementing algorithms or analyses in a scientific programming language
- A strong background in statistics including probabilistic modelling and computational statistics or machine learning methods or in a related subject
- Knowledge of a programming language adequate to computational statistics or machine learning methods
Full details of the role can be found on the Job Description.
The position is fixed term for 24 months. The expected start date is 1 February 2023 or soon thereafter.
*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the Level A salary range, £38,194 - £41,388 per annum.
In addition to completing the online application, candidates should attach:
- A full CV,
- A 1-page research statement describing why the candidate’s expertise is relevant to this position and future research plans; and
- The details of three referees.
For any specific queries regarding the post please contact Dr Sarah Filippi, (firstname.lastname@example.org).
The College is a proud signatory to the San-Francisco Declaration on Research Assessment (DORA), which means that in hiring and promotion decisions, we evaluate applicants on the quality of their work, not the journal impact factor where it is published. For more information, see https://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-evaluation/
The College believes that the use of animals in research is vital to improve human and animal health and welfare. Animals may only be used in research programmes which are ultimately aimed towards finding new treatments and making scientific and medical advances, and where there are no satisfactory or reasonably practical alternatives to their use. Imperial is committed to ensuring that, in cases where this research is deemed essential, all animals in the College’s care are treated with full respect, and that all staff involved with this work show due consideration at every level. http://www.imperial.ac.uk/research-and-innovation/about-imperial-research/research-integrity/animal-research/
About Imperial College London
Imperial College London is the UK’s only university focussed entirely on science, engineering, medicine and business and we are consistently rated in the top 10 universities in the world.
You will find our main London campus in South Kensington, with our hospital campuses located nearby in West and North London. We also have Silwood Park in Berkshire and state-of-the-art facilities in development at our major new campus in White City.
We work in a multidisciplinary and diverse community for education, research, translation and commercialisation, harnessing science and innovation to tackle the big global challenges our complex world faces.
It’s our mission to achieve enduring excellence in all that we do for the benefit of society – and we are looking for the most talented people to help us get there.
Please note that job descriptions cannot be exhaustive, and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.
Imperial College is committed to equality of opportunity and to eliminating discrimination. All employees are expected to follow the Imperial Values & Behaviours framework. Our values are:
In addition to the above, employees are required to observe and comply with all College policies and regulations.
We are committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment for all. We therefore encourage candidates to apply irrespective of age, disability, marriage or civil partnership status, pregnancy or maternity, race, religion and belief, gender reassignment, sex, or sexual orientation. We are an Athena SWAN Silver Award winner, a Disability Confident Leader and a Stonewall Diversity Champion.
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