PhD in Data- and AI-based Solutions for Child Health through Housing
Develop data-driven AI solutions to evaluate and optimize housing improvements for children's health and wellbeing.
Best for:Best for quantitative science or engineering graduates with strong Python programming and big data experience.
Overview
Eindhoven University of Technology is offering a four-year PhD position focused on creating innovative data-driven solutions to predict and optimize the impact of housing upgrades on children's health and development. Working within the Urban Systems and Real Estate group, the researcher will collaborate with an interdisciplinary team combining medical insights, large-scale data analysis, computer vision, and advanced statistical methods. The project forms part of the NWO-funded research programme Homes for Upcoming Generations, aiming to build predictive models and digital tools for municipalities and housing providers. Candidates are expected to engage in cutting-edge research, contribute to teaching tasks up to 15 percent, and participate in international conferences and advanced training.
What you'll do
- Develop innovative data-driven solutions and predictive models using complex unstructured housing and health data.
- Apply big data analysis, computer vision, and advanced statistical methods to assess housing upgrade impacts.
- Contribute to the creation of a digital tool designed to help municipalities and housing providers optimize housing interventions.
- Collaborate closely with interdisciplinary academic partners and societal stakeholders including housing providers and engineering bureaus.
- Fulfill teaching and educational duties corresponding to a minimum of 10% and a maximum of 15% of the annual employment time.
- Participate in advanced courses, seminars, and international conferences for professional development.
Requirements
Degree required: MSc degree in Exact or data sciences, Quantitative economics, or Engineering
Degree offered: PhD
Language: English; strong proficiency in spoken and written English
Instruction: English
- Proven programming experience in Python
- Demonstrated ability to work with big data and quantitative datasets
- Strong educational background including calculus, linear algebra, computational modeling, microeconomics, econometrics, operations research, or data science
- Demonstrable analytical skills and capability to bridge fundamental and applied research
- Affinity for collaborating with industry partners and interdisciplinary teams
Funding & terms
How to apply
Deadline: 2026-11-15
Submit your application including all required documents through the university's online recruitment portal by the specified deadline.
- CV
- Cover letter
- MSc transcripts
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