We are looking for two PhD students to work within the project ‘Understanding fundamental causes and effects of socio-economic inequalities in health using a systems science approach’, funded by ZonMw. This is a collaboration between the Academic Medical Center, the Computational Science Laboratory and the Institute for Advanced Study, and the Faculty of Social and Behavioural Sciences, all at University of Amsterdam.

The link between socio-economic status (SES) and health is complex, involving multifaceted, dynamic causal pathways, relating to money, knowledge, prestige, power, beneficial social connections etc. The aim of this project is to provide a fundamentally new understanding of the complexity and dynamics of the link between SES and associated resources to health, using a systems science approach. A system dynamics model (SDM) will be developed, in an iterative process, from empirical (epidemiological, ethnographic) and in-silico (computer simulation) studies. Integration of these approaches will help to identify leverage points in the system that have the potential to reduce health inequalities. We will use type 2 diabetes mellitus (T2D) as a case study.

Within this project, the two PhD students will work closely together.
As a PhD student ‘public health’ you will develop a conceptual model that maps the system that produces health inequalities. In addition, you will do statistical analyses based on data from the HELIUS study (www.heliusstudy.nl), linked to environmental data, including data on social networks. The outcome of these analyses serves as input for the SDM, which will subsequently serve to identify  leverage points that can ultimately lead to a reduction of health inequalities.
As a PhD student ‘computational modelling’ you will contribute to advancing computational methods. Your main aim is to deliver an integrated modelling framework that is able to use data from a number of sources: public health, clinical studies and social sciences; and provide a proof of concept. To do so you will contribute to the development of social network models based on complex networks and to an existing SDM of T2D. You will also integrate these models into a network of models, a computational framework to study the impact of policies on health inequalities.
Both PhD students will publish the result of their work in scientific journals and both trajectories will result in a dissertation. This will include reflections on the applicability of the developed methods for other health outcomes and settings.

The candidate for the PhD position ‘public health’ should have a master degree in epidemiology, health sciences, medical biology or a related discipline; strong epidemiological skills are a requirement.

The candidate for the PhD position ‘computational modelling’ should have a Master degree either in Computational Science, Applied Mathematics, Bioinformatics, Physics or related disciplines. The applicant should have experience in modelling and simulation, with good knowledge of modern computing environments such as Python. Experience with systems dynamics modelling and/or complex network modelling is preferred. Experience with, or willingness to learn required computer science technologies to integrate individual models into a unified framework is required.

Both candidates should:
- have a strong analytical mindset;
- have an ambition and drive to acquire a good understanding of public health;
- be able to work in an international multidisciplinary team;
- be willing to form a bridge between several disciplines within the project (public health, modellers, social scientists) and be capable to ‘speak their languages’.

Apart from a curriculum vitae and motivation letter, applications must include:
- a copy of your Master’s thesis;
- a complete record of Bachelor and Master courses (including grades);
- the names and contact information of two academic references (please do not include any recommendation letters).

The appointment will be on a temporary basis for a period of four years (initial appointment will be for a period of 18 months and after satisfactory evaluations it can be extended to a total duration of four years) and should lead to a dissertation (PhD thesis). Periodic evaluations will be held after nine and 14 months. An educational plan will be drafted that includes attendance of courses, summer and/or winter schools and (international) meetings. The PhD candidate is also expected to assist in teaching of undergraduates.

Based on a full-time appointment (36 hours per week) the gross monthly salary will range from EUR 2.279,00 in the first year, to EUR 2.919,00 in the fourth year. Holiday allowances of 8% and end year payment 8.3% of the gross yearly salary.

The PhD students will work an ambitious environment, with excellent supervision, and  critical, open-minded and inspiring interactions with scientists from a broad range of disciplines. Excellent computer facilities are offered for the PhD computational modelling.

AMC Medical Research

The AMC is more than just a hospital. It is a world in which patient care, research and education are integrated, and in which people are always central. It is an academic world full of possibilities for talented individuals that are looking for a place where they can excel. Thinking big, daring to dream, cooperating internationally. And never letting yourself be put off by ‘It’s not possible’ or ’It won’t work anyway’. That is the AMC mentality.

http://www.amc.nl/

The mission of the Department of Public Health of the AMC is to perform high quality research in the field of public health, health promotion and health services research. This research aims to contribute to the scientific evidence that is needed to support policies aimed at fostering and improving the health of populations at local, national and international levels. Particular attention is given to the health situation and health care needs of socio-economically deprived groups.

The mission of the Computational Science Laboratory of the University of Amsterdam is to perform curiosity driven and use-inspired fundamental research in Computer Science. The research in the institute involves complex information systems at large, with a focus on Collaborative, Data Driven, Computational and Intelligent Systems, all with a strong interactive component .