research assistant South Kensington, England
Job description
This is an exciting opportunity to help lead an ongoing programme of methodological research to tackle pressing global health problems in collaboration with leading international organisations.
The focus of this post is on the development of novel, flexible and computationally tractable spatio-temporal statistical inference tools in Bayesian Statistics and AI, and on their application in three domains.
Applications range from HIV deep-sequence phylogenetics within the PANGEA-HIV consortium, to quantification and hotspot mapping of caregiver loss with the Global Reference Group for Children Affected by COVID-19 and in Crises, and species mapping and forecasting using oceanographic and climatological datasets.
You will have access to some of the finest longitudinal datasets in Africa and South America. Post holders will interact with a team of leading researchers. They will receive hands-on training in machine learning and modern statistics, epidemiological, and phylogenetic techniques, and will be mentored by leading scientists, who often publish in some of the top journals of the field.
Your base will be in the Department of Mathematics, and you will work closely with the Machine Learning & Global Health Network (MLGH), a multi-institution research laboratory with members at Oxford, Imperial College London, University of Copenhagen, and Singapore.
Duties and responsibilities
Post holders will be reporting directly to Dr Oliver Ratmann (Imperial), and collaborating closely with Professor Seth Flaxman (Oxford), Dr Kate Grabowski (Johns Hopkins), Dr Ettie Unwin (Bristol), Dr Adam Sykulski (Imperial), and Professor Christophe Fraser (Oxford).
The proposed research aims at the further development of novel spatiotemporal methods in deep-sequence phylogenetics (building on recent work as in Monod et al., 2023, Blenkinsop et al., 2023, Golubchik et al., 2022, Semenova et al., 2022); and spatiotemporal methods for quantifying and mapping caregiver loss (building on recent work as in Hillis et al, 2021, Hillis et al, 2022).
Key external partners include the World Health Organization, the US Centers for Disease Control and Prevention, the Stan Development Team, PANGEA-HIV, the World Bank, UNAIDS, and the British Antarctic Survey. In addition to research, you will help train practitioners in partner organisations. You will also have the opportunity to participate in teaching and in the supervision of undergraduate and postgraduate students.
You will be expected to communicate research findings to other researchers, through conference and journal publications, and policymakers, through international meetings; demonstrate research independence in the conception and execution of methodological research; disseminate replicable and reproducible data scientific workflows and help train practitioners in the use of new methods.
We would particularly welcome applications from the global South, women, black and minority ethnic applicants who are currently under-represented within the Department of Mathematics.
Essential requirements
The essential requirements for this post include:
- The successful candidate will hold A PhD (or equivalent or close to completion) in Statistics, Mathematics, Global Health, Ecology, or a field related to the Programme *Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.
- Experience of research in modern Bayesian statistics, computational statistics, or statistical machine learning.
- Experience of writing research papers.
- Experience in giving talks at internationally recognised conferences and workshops.
- Experience in carrying out research of high quality, independently and in a team, evidenced by publications of high quality.
- Experience collaborating with applied scientists or policy makers.
- Clear evidence of outstanding promise and originality in research, with a good publication record, commensurate with career stage.
- Knowledge of spatial statistics, time series, or network statistics.
- Knowledge of probabilistic programming languages (e.g. Stan, TMB, PyMC, Pyro, Numpyro).
Further information
The position is fixed term for 12 months, with possible extension. The expected start date is 01 October 2023 or soon thereafter. You will be based at South Kensington Campus.
- Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range, £38,194- £41,388 per annum.
In addition to completing the online application, candidates should attach:
- A full CV,
- A 2-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 and discuss your interest, please contact Dr Oliver Ratmann, [email protected]
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. Find out more about animal research at Imperial.
