Important Info
Please submit your application materials to kvonner@stanford.edu
The Building for Wellbeing Lab seeks a Post-doctoral Scholar with a vision for the design of sustainable built environments to foster human wellbeing supported by engineering and social science research. Our projects span multiple schools and centers at Stanford University as well as external collaborations with other universities and municipal and non-profit partners. This highly collaborative environment provides many professional growth opportunities in academia and beyond for those with interests in engineering with social impact.
We are examining how civilian-led safety interventions and neighborhood environments affect community wellbeing. One project evaluates the impacts of urban civilian safety practitioners using AI-driven multimodal sensing to understand mechanisms of de-escalation and disorder reduction in San Francisco, CA. A second project uses a mobile crowdsensing system and computer vision techniques to identify neighborhood environmental features and their relationships with community and resident wellbeing with an initial focus on San José, CA. Both projects are in their early stages and will provide ample opportunities to lead and build out.
Your responsibilities include:
- Develop and manage research programs by conducting research that supports and expands the impact of projects conducted in the Lab, particularly related to multimodal sensing, AI/computer vision applications, and community-engaged research
- Identify, recommend, and implement opportunities for new research at the intersection of built environment and wellbeing
- Source, collect and analyze data from sensors, community observations, official records, and surveys; create reports, review and explain trends; formulate and evaluate alternative solutions and/or recommendations to achieve the goals of the research program
- Co-design sensing methods and protocols with community partners, residents, and municipal stakeholders
- Conduct field experiments and pilot tests; refine detection algorithms and sensor deployment strategies
- Write and/or edit content for proposals, research grants, and peer-reviewed publications
- Advise and mentor undergraduate and graduate students
- Present research, represent the Lab at relevant conferences, and participate in relevant programming on campus
- Doctoral degree in engineering (civil/environmental engineering, urban planning, computer science, electrical engineering); preferably having collaborated with social scientists
- Expertise in machine learning, particularly in computer vision and in relation to multimodal sensing data, mobile crowdsensing technology, and predictive modeling
- Strong data analysis and statistical skills to quantify community wellbeing
- Knowledge of urban studies and preferably with a background in behavioral sciences and/or environmental psychology
- Proficiency in programming languages (e.g., Python or R) is essential
- Demonstrated ability to collaborate across disciplines
- Strong communication skills and an understanding of ethical considerations in community engagement and with vulnerable populations
- Creative, self-motivated, able to identify research opportunities independently
- Strong writing skills with ability to publish in peer-reviewed journals
- CV
- A research statement describing your interest and experience related to the two projects of focus for this position. (1 page max)
- A brief statement on your vision for the design of sustainable built environments to foster human wellbeing supported by engineering and social science research (1 page max)