To strengthen our section Child & Adolescent Public Health Research & Innovation in Amsterdam, we are looking for a Mid-Career Researcher in the area of Youth 24-hour Physical Activity, the (Urban) Environment and Methodological Innovations, starting from 1 February 2023. The candidate is expected to coordinate a program of research on methodological innovations in research on 24/7 movement in youth, specifically as part of two European Commission funded projects. Relevant methodological approaches including Participatory Action Research, Inclusive Research, Complexity Science, Realist Evaluation, Mixed Methods analyses, and Multimodal Data Analysis.
Your challenge is to contribute to two prestigious EC funded projects in the field of 24-hour Movement Behavior and Health in youth: YoPAAPE and the Marie Curie Doctoral Network LABDA. The aim of YoPAAPE is to reduce the risk of non-communicable diseases among teenagers in vulnerable life situations, via evidence-based co-creation of social and physical environmental interventions in Europe and Africa. In LABDA, 13 doctoral fellows are trained to establish novel methods for advanced accelerometer 24/7 movement behavior data analysis and assess the added value of linking multimodal data, creating an open source toolbox of advanced analysis methods.About your role
Your specific responsibilities will be to:
- Co-coordinate EC-funded projects together with the project coordinator prof Chin A Paw (e.g. participation in consortium meetings; participate in training; communication with EC);
- Collaborate with and support ongoing PhD projects on 24/7 movement behavior and co-creation of the social and physical (Urban) Environment;
- Develop novel theoretical and methodological approaches regarding 24/7 movement behavior and the evaluation of social and physical (Urban) environmental interventions that are developed via participatory methods;
- Develop and write new grant proposals;
- Dissemination of research findings through e.g. peer reviewed journals, presentations, lectures and media in various way;
- Contribute to advanced statistical analyses of device-derived (e.g. accelerometers, inclinometers) and environmental data;
- Contribute to education of BSc, MSC and PhD students in Health Science, Medicine and Human Movement Science.