Key Skills

Job Description

Introduction Are you a graduate in exact sciences, engineering or econometrics, passionate about using data and AI to improve people's lives?Eindhoven University of Technology is looking for a PhD candidate to develop innovative data-driven solutions that predict and optimise the impact of housing improvements on children's health and wellbeing. Job Description Millions of children, even in high-income countries, are born and grow up in homes with poor insulation, inadequate heating, or insufficient ventilation, affecting their health and development. While housing upgrades are often motivated by sustainability and affordability goals, we focus on their potential benefits for future generations. How does inadequate housing during pregnancy and early childhood affect children's health and development? Which housing upgrades offer the greatest benefits? And how can behavioural modelling, big data and AI help shape healthier, more equitable homes? These are the questions your PhD research will tackle. You will join an interdisciplinary team of researchers and practitioners, working at the intersection of housing, public health, climate adaptation, and social equity. Combining medical and behavioural insights, large-scale data analysis, computer vision and advanced statistical methods, you will be tranforming complex unstructured housing and health data into predictive models. The results will feed into a digital tool to predict and optimise the impact of housing upgrades across different scenarios, helping housing providers and municipalities create healthier, more resilient homes for families. This research is part of the NWO-funded research programme Homes for Upcoming Generations, which brings together social scientists, medical doctors, building engineers and industry partners. As a PhD candidate, you will be part of the TU/e's internationally renowned Urban Systems and Real Estate group (Department of the Built Environment), conducting cutting-edge research at the intersection of urban systems, real estate, data science, and smart technologies. The four-year program combines advanced training with impactful research, offering strong support for professional development through courses, seminars, and international conferences. You will collaborate closely with scientific partners at Erasmus Medical Centre, Erasmus University Rotterdam, VU University Amsterdam, as well as societal partners including housing providers, municipalities and engineering bureaus. Job Requirements The candidates should have: An MSc degree in Exact or data sciences/ Quantitative economics/ Engineering. A strong educational track-record including at least several of the following subjects: calculus, linear algebra, computational modelling, microeconomics, econometrics, operations research, data science. A proven experience of programming in Python and working with (big) data. Having working experience at a European research institute or a European university is an advantage. Strong demonstrable analytical skills and proficiency in English (spoken and written). Affinity with collaboration with industry, ability to bring together fundamental and applied research. Conditions of Employment A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In Addition, We Offer You Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment. Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,204 - max. € 4,051 gross base salary per month (full-time)). In addition to your base salary, you will receive an 8% holiday allowance and an 8.3% year-end bonus, both calculated based on your annual gross base salary. Generous leave options: a standard 29 days (based on a 38 hour working week) per year that you can increase to 41 days by working two hours more per week (flexible working hours). This is prorated if you work part-time. As a TU/e employee, you participate in the ABP pension scheme, providing retirement pension and pension benefits for surviving dependents and occupational disability. TU/e pays 70% of the pension premium, while employees contribute the remaining 30%. High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process. An excellent technical infrastructure, and on-campus children's day care. Unlimited access to the modern on‑campus TU/e Student Sports Center at an exceptionally affordable rate. We support your wellbeing with free 24/7 access to OpenUp, providing you and your family with mental health support, expert guidance, and online training. An allowance for commuting, working from home and internet costs. A Staff Immigration Team and a tax compensation scheme (the Expat Scheme) for international candidates. On our website you can discover even more information about our conditions of employment. Build on your career at TU/e! About Us We are a leading international university where scientific curiosity meets a hands-on mindset. We work in an open and collaborative way with high-tech industries to tackle complex societal challenges. Our responsible and respectful approach ensures impact — today and in the future. TU/e is home to over 13,000 students and more than 7,000 staff, forming a diverse and vibrant academic community. Discover what Light Up means to TU/e in our short company video. Our university is located in Brainport Eindhoven — a world‑leading tech region with more than 7,000 high‑tech companies and strong R&D activity. Known for breakthroughs in AI, photonics, semiconductors and advanced manufacturing, Brainport is a place where technology serves people and society. Learn more about the Brainport region here. Information Do you recognize yourself in this profile and would you like to know more? Please contact the hiring manager Leo van Houten, e-mail: [email protected], phone: 040 – 247 8269. Visit our website for more information about the application process. You can also contact Ioulia Ossokina, Associate professor, [email protected]. Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video. Are you inspired and would like to know more about working at TU/e? Please visit our career page. Application We invite you to submit a complete application by using the apply button. The application should include a: Cover letter in which you describe your motivation and qualifications for the position. Curriculum vitae, including a list of your publications and the contact information of three references. Kindly note that we may reach out to references at any stage of the recruitment process. We recommend notifying your references upon submitting your application. Ensure that you submit all the requested application documents. We give priority to complete applications. We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled. Please note You can apply online. We will not process applications sent by email and/or post. A pre-employment screening (e.g. knowledge security check) can be part of the selection procedure. For more information on the knowledge security check, please consult the National Knowledge Security Guidelines. Please do not contact us for unsolicited services.

Core Responsibilities

Conduct interdisciplinary PhD research on how housing conditions and upgrades affect children's health and development, using large-scale data, computer vision, behavioral insights, and statistical methods. Develop predictive models and contribute to a digital tool that helps housing providers and municipalities assess and optimize the health impacts of housing improvements.

Requirements

Applicants must have an MSc in exact or data sciences, quantitative economics, or engineering, with a strong academic background in relevant quantitative subjects. They should have proven Python programming and big-data experience, strong analytical skills, English proficiency, and an interest in collaboration between fundamental research and industry; European research or university experience is an advantage.

Benefits

• Pension Scheme
• Paid Pregnancy And Maternity Leave
• Partially Paid Parental Leave
• Holiday Allowance
• Year-End Bonus
• Generous Annual Leave
• Professional Training And Development
• On-Campus Childcare
• Access To On-Campus Sports Center
• Mental Health Support
• Commuting Allowance
• Work-From-Home Allowance
• Internet Cost Allowance
• Tax Compensation Scheme For International Candidates