2 PhD positions on Computational Methods for Environment-related Exposures

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.

We are looking for motivated young researchers with a background in (A) computer science, data science, geographic information science, geomatics, or related disciplines and (B) computer science, data science, industrial design, urban/regional planning, or related disciplines. Candidates should have the following qualifications:

• A Master’s degree in one of the aforementioned disciplines
• Willingness to work in a multidisciplinary context at the interface   of  academia and design-led research
• Aptitude for independent work
• Good team working skills
• Excellent English oral and writing skills
• Good programming skills in Python, R, and/or other related languages
• Experience with software development (both backend and frontend) would be considered as advantage.

TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit http://www.tudelft.nl/phd for more information.   

Delft University of Technology (TU Delft) is a multifaceted institution offering education and carrying out research in the technical sciences at an internationally recognised level. Education, research and design are strongly oriented towards applicability. TU Delft develops technologies for future generations, focusing on sustainability, safety and economic vitality. At TU Delft you will work in an environment where technical sciences and society converge. TU Delft comprises eight faculties, unique laboratories, research institutes and schools.

The faculty of Industrial Design Engineering is the largest and broadest scientific design institute in the world, with over 2,000 students, more than 6,000 alumni and 300 staff (researchers and lecturers, including designers from industrial practice). The faculty aims to contribute to a better living environment and respond to social challenges by combining human values and desires with technological feasibility and economic viability. We are excellently placed to do so, as we ground design methods and skills in scientific knowledge from a wide range of disciplines, leading to concrete solutions.

The faculty of Industrial Design Engineering consists of three departments: Industrial Design Engineering (ID), Design Engineering (DE) and Product Innovation Management (PIM). The Design Engineering Department is a centre for sustainable system-oriented product-service development, innovation, and manufacturing. The aim of our work is to empower designers through breakthrough technology innovations and to contribute to the innovative capability and competitiveness of the creative industry sector. The Design Engineering Department comprises more than twenty faculty members with research interests in cyber physical systems, intelligent products, internet of things, digital fabrication & 3D printing, data-intensive systems, augmented reality, human-robot collaboration, and sustainable design.

The successful candidate will join the Data and Intelligence section at the Department of Design Engineering led by Prof. Gerd Kortuem and Prof. Alessandro Bozzon, a growing research group comprising experts in Artificial Intelligence, Smart Cities, Internet of Things, Data Analytics, Crowd Computing, Human-Robot Collaboration and Design. The key mission of this group is to develop innovating methods for the design and engineering of next-generation intelligent products, services and systems. The candidate is expected to contribute a human-centred perspective to existing expertise.