06 Postdoctoral Fellowship at London School of Hygiene and Tropical Medicine, United Kingdom

This is an 18 month Research Assistant position, with the successful candidate embarking on a PhD programme at LSHTM. It is anticipated that the role will lead to a further 18 month funded opportunity at Max Planck Institute for Demographic Research (MPIDR), in Germany, subject to MPIDR terms and conditions.

The role is based within the Mortality and Inequalities Research Group at LSHTM with close partnership with the Department of Digital and Computational Demography at MPIDR. José Manuel Aburto (LSHTM) and Emilio Zagheni (MPIDR) will supervise the successful candidate. 

This position is an excellent opportunity for highly-motivated and qualified candidates to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human mortality using traditional and new forms of data, with a focus on developing and low-income countries. 

The successful applicant will spend 18 months at LSHTM and enrol in the PhD programme, with fees funded by LSHTM for the duration of the programme.  It is anticipated that the role will lead to a further 18 month funded opportunity in residence at MPIDR, in Germany, which would be subject to MPIDR terms and conditions. The successful candidate is expected to enrol in the MPIDR IMPRS-PHDS programme from the beginning of their doctoral training at LSHTM, which provides further opportunities for training and networking. They will be working within a vibrant community of research degree students and researchers at both institutes. 

The Research Fellow will conduct statistical analyses on national and sub-national survey data collected through a new Gates Foundation-funded initiative at the Vaccine Confidence Project, focused on the Immunisation Metrics and Monitoring Systems (IMMS). This global project aims to assess the behavioural and social drivers of vaccine uptake and to identify both supply- and demand-side barriers to immunisation. The post-holder will contribute to modelling vaccination barriers and facilitators, develop forecasts of vaccine coverage for existing and novel vaccines (e.g. HPV, RSV, malaria), and support the design and implementation of small area estimation and reweighting strategies in data-scarce settings.

We are seeking a researcher with skills in quantitative data analysis to join a dynamic team that has, for the past 8 years, developed an extensive body of research on corruption, governance and anti-corruption strategies. In the Accountability in Action project (Understanding and eliminating district-level corruption in the health sectors in Nigeria and Malawi), we have pioneered a novel approach seeking to identify the institutional and structural drivers of corruption, and seeking to identify feasible anti-corruption strategies.

The post holder will lead the analysis of household surveys, in Enugu and Kano states of Nigeria, and in Malawi, exploring user experiences of illicit practices, impact on health care seeking, and perception of actors involved. This is a fantastic opportunity for a researcher to lead and contribute to analysis and write up of high-profile papers on governance and (anti-)corruption, and participate in academic and policy engagement activities. Given our commitment to equitable partnerships, they will be supporting researchers in Malawi and Nigeria to further develop their analysis, and write up papers. They will lead and contribute to analyses utilizing existing global datasets (e.g. Corruption Perception Index, V-Dem, etc.) exploring the relationships between corruption, service delivery and outcomes.

We are recruiting a medical statistician to join an exciting research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models for cardiovascular disease in this patient group using linked electronic health record data. The post offers an excellent opportunity to develop expertise in risk prediction methodology for electronic health records.

Based at LSHTM in London the post-holder will be embedded within the Electronic Health Records Research Group and will work closely with external collaborators. 

The post-holder must have a postgraduate degree, ideally a doctoral degree, in a relevant topic. The post requires strong quantitative skills with expertise in a common statistical package such as Stata/R and the ability to work with large datasets. Some experience with observational data analysis and familiarity with risk prediction is required. A commitment to multi-disciplinary and collaborative working is essential. Experience using electronic health records, especially for risk prediction, is desirable. Further particulars are included in the job description.