2 PhD positions on Computational Methods for Environment-related Exposures at Delft University of Technology

The PhD positions are part of a funded Horizon 2020 research project, entitled “Equal-Life: Early environmental quality and life-course mental health effects”. The project will develop and test combined exposure (exposome) data using a novel approach to multimodal environment-related exposures (e.g. quality of neighborhood in urban areas, access to amenities, air pollution, noise, proximity to green spaces, natural light, social safety, social interactions, among others) and their impact on children’s mental health and development. It will do this at different scale levels and timeframes – through the combination of birth-cohorts and new sources of data – while accounting for the distribution of exposures in social groups based on gender, ethnicity, and social vulnerability.

The project comprises a consortium of experts from twenty major academic, governmental, and industry institutions: RIVM, Göteborgs Universitet, TU Delft, TU Eindhoven, Karolinska Institutet, TU Kaiserslautern, TU Graz, University of Leicester, Universität Bremen, Universiteit Gent, Gemeente Utrecht, and others.

The PhD positions focus on, respectively:

A.Computational Methods and Tools for Multimodal Exposome Data Collection and Enrichment
The PhD candidate will explore and develop novel methods for exposome data collection and enrichment, based on new and complementary data sources (e.g. social media, public fora, online map data, street-level imagery, crowdsourcing campaigns etc.). The successful candidate will also develop methods, tools, and evaluation results for crowd-based creation and enrichment of exposome data, as well as mechanisms and interface mock-ups for the incentivization and retainment of crowd contributors. The developed methods and tools will potentially facilitate the planning and design of interventions focused on children’s environments.

B.Intelligent Tools for Data-Driven Health Interventions
The PhD candidate will explore data visualization, data exploration, and semantic knowledge analysis techniques to test, refine, and adapt data-driven health interventions at the regional level. The successful candidate will design and develop tools that help deploy effective science- and data-based health interventions.

Further details:
2 PhD positions on Computational Methods for Environment-related Exposures at Delft University of Technology