PhD position: data analysis and mathematical/statistical modeling of data in the RSV vaccine field to design optimal RSV vaccination strategies
The PhD candidate will primarily be involved in data analysis and mathematical/statistical modeling of data. In addition, the candidate will be involved in daily supervision of supportive students involved in global data collection, and monthly meetings with the BMGF. The specific focus of the PhD student is to develop mathematical models that can inform stakeholders in the RSV vaccine field about the impact of upcoming RSV vaccines and extended half-life antibodies in order to optimize their administration in relation to seasonality and gestational age in different target populations.
Department
The candidate will work at the Center for Translational Immunology and the Pediatric Department. The PhD student will be supervised by Prof. Louis Bont (pediatrician specialized in infectious diseases and immunology), Dr. José Borghans and Dr. Julia Drylewicz (specialized in computational immunology and biostatistics). The PhD student will be embedded in the RSV GOLD team with 2 other PhD students and 15 medical students within the RSV Research Group, as well as in the computational immunology group at UMC Utrecht. Background Respiratory syncytial virus (RSV) infection is an important cause of morbidity and mortality in young children. Globally, it is estimated that 48000-74500 children aged younger than five years died in-hospital with RSV-related lower respiratory tract infection in 2015. About 99% of RSV-related childhood mortality occurs in developing countries. Children with underlying comorbidities such as premature birth, congenital heart disease or chronic lung disease are at increased risk for severe or even fatal RSV infection. Most RSV-related mortality occurs during the first year of life. Currently, maternal vaccination is being considered for RSV prevention in young children. We have recently developed a mathematical model of antibody-transfer between mother and child taking into account transplacental antibody transfer and gestational age (Scheltema et al. Vaccine 2018) which suggested that maternal vaccination against RSV could substantially decrease global RSV-related in-hospital infant deaths. The project The aim of the current PhD project is to improve upon this model by including different factors that may influence the impact of maternal vaccination, including breast-feeding, seasonality, RSV transmission patterns and vaccine coverage. The RSV GOLD project – of which this modelling project will be part – is funded by the Bill and Melinda Gates Foundation (BMGF) and is the first global registry of children who have died with RSV infection. It aims to collect and analyze individual patient data of infants dying with RSV infection. The RSV GOLD project has a strong global health focus. More information can be found at www.rsvgold.com.
Profile
We are looking for an ambitious candidate with a Master’s degree in biostatistics/medical statistics/theoretical biology or proven expertise in mathematical modeling/biostatistics, as well as programming skills in R or Python, and a clear interest in biomedical research. Excellent communication skills are required to work in this dynamic and multidisciplinary research team.
The maximum salary for this position (100%) is € 3.103,00 gross per month based on full-time employment (work week 36 hours). This job is based on a temporary position for 4 years.
In addition, we offer an annual benefit of 8.3%, holiday allowance, travel expenses and career opportunities. The terms of employment are in accordance with the Cao University Medical Centers (UMC).
More information
If you have any questions about this vacancy, please contact Mr. Louis Bont, pediatrician, phone number: 088 755 4003, e‑mail address: l.bont@umcutrecht.nl.
Applying to the PhD position is possible via the following link:
https://www.werkenbijumcutrecht.nl/vacatures/Paginas/phd-student-in-het-wilhelmina-kinderziekenhuis%20(2020-0196).aspx
Acquisition based on this job opening is not appreciated.
