Project Mentor
Dr. Hanlin Zhou
Department: Geography, Sustainability, Community, and Urban Studies
Project Overview:
The project integrates methods from cognitive science, geospatial analysis, and artificial intelligence to investigate how people perceive environmental risk in their surroundings and to identify the key visual features in real-world landscapes that shape such judgments.
Role of a SHARE Summer Apprentice:
The SHARE apprentice will contribute to two areas of the project. First, the apprentice will assist with the preprocessing and screening of georeferenced street view images used as visual stimuli in the study. Second, the apprentice will support outreach and participant recruitment online by distributing recruitment materials, managing posts on approved social media platforms and email channels, contacting community centers and survey companies, and tracking publicly available engagement metrics to help optimize recruitment strategy.
Through this experience, the apprentice will gain hands-on skills in geospatial data survey collection, as well as firsthand practical experience in online community engagement of research activities.
The apprentice will receive structured training and ongoing mentorship throughout the appointment. During the first two weeks, the PI and graduate research assistant will provide an orientation covering the project’s research goals and the basics knowledge of the research, so the apprentice understands the broader scientific context of their contributions. The apprentice will also complete required human subjects research ethics training and receive a focused briefing on the study’s IRB protocol, including participant confidentiality requirements and the boundaries of their role.
For the image preprocessing task, the PI and graduate research assistant will train the apprentice on the processing techniques and quality standards used to evaluate georeferenced street view images, including hands-on walkthroughs of example cases. The apprentice will initially work on small batches with close review from the research team before progressing to independent work. For the outreach task, the PI and graduate research assistant will work with the apprentice to contact survey companies and community centers for building survey and collecting data.
The PI and graduate research assistant will hold weekly one-on-one check-in meetings with the apprentice to review progress, provide feedback, and discuss any challenges. Throughout the program, the PI and graduate research assistant will encourage the apprentice to reflect on their learning experience and will provide mentorship on academic and career development, including guidance on pursuing future research opportunities.
Summer Schedule/Time Commitment:
The apprenticeship is designed to be flexible and task-based. There are no required days or fixed hours. The apprentice may complete their work at times that best fit their own schedule, as long as agreed-upon deadlines are met for assigned tasks. The expected workload is approximately 10 hours per week, though this may vary slightly depending on the phase of the project. The apprentice will attend one regular check-in meeting with the PI and graduate research assistant each week, while the specific day and time will be determined at the start of the appointment based on mutual availability. The apprenticeship can readily accommodate other summer commitments the student may have. We ask only that the apprentice communicate their availability and any scheduling constraints in advance so we can plan tasks accordingly.
Preferred Qualifications:
We welcome applicants from any major or academic background. We are looking for students who have experience with outreach, communication, or community engagement, and are comfortable reaching diverse audiences through social media and email channels. We value an enthusiastic, outgoing disposition and the ability to communicate clearly and effectively on behalf of a research team. Students with work experience in Student Union or off-campus NGO are highly encouraged to apply.
While this project includes geospatial data survey, familiarity with GIS data organization and file management is helpful but not required. Additionally, no prior research experience or AI skills are needed. The most important qualities are reliability, willingness to learn, and strong communication with the research team about progress and availability.
To Apply:
The application opens on Monday, March 2, 2026. Click here to submit an online application for this SHARE apprenticeship through the Quest Portal. The application deadline is Monday, March 30, 2026, at 11:59pm.