Tropical diseases affect more than one billion people, costing developing economies billions of dollars every year. They remain a formidable challenge to the achievement of the Sustainable Development Goal 3 (SDG-3) of ensuring healthy lives and promote well-being for all at all ages. The current sobering trends of tropical diseases like diarrhea, cholera, malaria, typhoid, and intestinal worms within the sub-Sahara Africa region are the realities of these challenges. There is considerable optimism about control and reductions in morbidities if knowledge of the spatial dynamics and environmental determinants is well explored. Spatial statistics, when integrated with geo-information and epidemiologic studies, can lead to the understanding of the nature of spatial patterns, the temporal dynamics, and the predisposing factors that contribute to infection.

This PhD research aims to develop spatial, temporal, and spatiotemporal models that associate overburdened tropical diseases with environmental, socioeconomic, demographic and climatic exposures. As inter­disciplinary research it integrates public health and epidemiology with spatial statistics. Research will focus on the use of both primary and secondary data from existing health management information systems within the Sub-Saharan Africa setting. The combined exposure effects of space, time, and space-time will lead to highly parameterized models. The prospective PhD candidate should have the eagerness to explore the use of Hierarchical Bayesian estimation method since it allows flexible modeling and inference and provides computational advantages via the implementation of Markov chain Monte Carlo (MCMC, WinBUGS/JAGS, STAN) methods or Integrated Nested Laplace Approximation (INLA).

The study will be in collaboration with the Ghana Health Services (GHS) and Kwame Nkrumah University of Science and Technology (KNUST)-Ghana.

• You have an MSc degree in public health, biostatistics, geomatic engineering or environmental engineering or data science.
• You have expertise in acquisition and processing of geo-information & remote sensing data.
• You have good knowledge in spatial data analysis and excellent programming skills in R, or python
• You have demonstrated scientific creativity that has preferably resulted in a scientific publication.
• You have excellent communication skills and good English language proficiency
• You have familiarity with the sub-Saharan Africa region and willing to spend about 6 months gathering data in this region.
• You have an affinity with a multi-cultural education environment, excellent work ethics, and commitment to the job

We offer a position in an inspiring and challenging multidisciplinary and international environment for a period of four years. Salary and conditions will be in accordance with the Collective Labour Agreement (CAO) for Dutch Universities:

• A starting salary of € 2,395.00 in the first year and a salary of € 3,061.00 in the fourth year gross per month;
• A holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.3%;
• A solid pension scheme;
• Minimum of 41 holiday days in case of full-time employment;
• Professional and personal development programs;
• Costs for moving to Enschede may be reimbursed.