PhD prevention models of virus-related cancers

This PhD position is in the field of cancer prevention. About one in eight cancers worldwide is attributable to an infectious cause, and many of these cancers are preventable by vaccination or screening plus treatment at an early (precancerous) stage.

To decrease the burden of infection-related cancers, the EU has funded a Joint Action initiative – entitled SHIELD – which aims to devise a comprehensive and effective prevention programme throughout the European continent. Within this initiative, Amsterdam UMC leads the task to map the burden of cancers attributable to hepatitis B virus (HBV) and human papillomavirus (HPV) across Europe, and to evaluate the impact and the cost-effectiveness of preventive measures. The focus is on vulnerable and underserved groups facing heightened risks and limited access to healthcare.

As a PhD student, you will be involved in the further development of a general framework for impact and cost-effectiveness assessments, such as semi-Markov models linked to disease transmission models. The framework builds on existing models but these must be adapted to account for differences in epidemiology and disease burden between regions and relevant populations, and allow for impact comparisons between different vaccination and screening strategies in high-risk groups (e.g. sexual minorities and migrant populations).

Your main tasks are to: 

• develop a general framework for impact and cost-effectiveness evaluations of preventive measures against HBV and HPV;
• perform an impact comparison between countries with different HBV and HPV vaccination and screening programmes;
• evaluate how screening strategies are related to vaccination coverage at a population level, and assess additional measures for vulnerable groups;
• contribute to the overall goals and objectives of SHIELD;
• publish your research findings in peer-reviewed scientific journals;
• write a PhD thesis for defence at the Vrije Universiteit Amsterdam.

You are a computational biologist, biostatistician, econometrician or health economist with strong modelling and programming skills and an interest in public health. You have the following expertise: 

• MSc degree in (mathematical or computational) biology, (bio)statistics, econometrics or closely related field;
• modelling skills and programming experience, preferably in R and C++ (or Python, Java or similar);
• clear interest in the field of biomedical or public health research;
• good communication skills and excellent command of English, and the ability to work in a multi-disciplinary environment.