2025 FALL - ONE PH.D. POSITION IN FALL 2025 AT URBAN AI LAB IS OPEN NOW (FULL TUITION & STIPEND)

One Fully Funded Ph.D. Position in Fall 2025 at the Urban AI Lab at the University of Florida is open for application now!

Urban AI Lab, directed by Prof. Shenhao Wang, is recruiting a fully funded Ph.D. student starting in Fall 2025, and the application starts in fall 2024.

Our work develops novel AI approaches to focus on three research themes: (1) travel behavior, (2) resilient and equitable urban systems, and recently (3) generative AI in cities (See details on our lab’s website: http://urbanailab.com)

Ph.D. candidate is expected to have the the following qualification:

• Bachelor’s or Master’s degree, with preference for majors in urban planning, civil/transportation engineering, geographic information systems. Relevant backgrounds in computer science, economics, statistics, architecture, and landscape design are also considered.

• Experience in mathematics and modeling, including experience in data analysis, machine learning, and statistical modeling.

• Experience in programming, particularly in Python or R.

• Strong English academic writing and communication skills.

• Demonstrated outstanding academic records and a passion for research

Interested Ph.D. candidates can send resume, undergrad transcript, and cover letter to Prof. Shenhao Wang at shenhaowang@ufl.edu

PhD applications will be reviewed and decided upon only after candidates have successfully completed their submissions through University of Florida application system. Please list Prof. Shenhao Wang as your advisor on the application form and research statement.

Apply here: UF Graduate Application

PAST PH.D. OPPORTUNITY

2024 Fall - Two Fully Funded Ph.D. Positions in Fall 2024 at the Urban AI Lab, University of Florida (Dr. Shenhao Wang) - COMPLETE

Dr. Shenhao Wang leads the Urban AI Lab at the Department of Urban and Regional Planning at University of Florida College of Design, Construction and Planning. The lab fuses artificial intelligence and behavioral science to develop fundamental theory for urban science, collaborating with top institutions and industry leaders: http://urbanailab.com. We are recruiting two Ph.D. candidates in Fall 2024, and the application starts in Fall 2023. The ideal Ph.D. candidate should have the the following capacity:

• Bachelor’s or Master’s degree, with preference for majors in urban planning, civil/transportation engineering, or geographic information systems. Relevant backgrounds in computer science, economics, architecture, and landscape design are also considered.

• Experience in mathematics and modeling, including experience in data analysis, machine learning, and statistical modeling.

• Experience in programming, particularly in Python or R.

• Strong English academic writing and communication skills.

• Demonstrated outstanding academic records and a passion for research

To apply, please send your resume and cover letter to Dr. Shenhao Wang (Email: shenhaowang@ufl.edu), detailing your GPA, research experience, publication history, and TOEFL scores in your resume. In your cover letter, explain your motivation for applying, your research interests, and why your past experiences make you a suitable candidate for this position.

To apply successfully, complete your application and submit required materials on UF Grad Online Application Portal (https://www.applyweb.com/uflgrad/index.ftl). When you apply, please explicitly state your interest in collaborating with Dr. Wang and outline specific research interests in your research statement.

2023 Fall - One Fully Funded Ph.D. Positions at the Urban AI Lab, University of Florida (Dr. Shenhao Wang) - COMPLETE

Dr. Shenhao Wang is looking for a candidate for a fully funded Ph.D. position, who can start the Ph.D. program in 2023 Fall with the application starting in 2022 Fall. The Ph.D. candidate is funded by fellowship or research assistantship, covering the tuition and the stipend. The research direction is urban artificial intelligence with a focus on behavioral modeling with deep learning. Please contact Shenhao Wang (shenhaowang@ufl.edu) if you are interested.

The ideal Ph.D. candidate should have the following capacity:

1. The candidate should have a long-term goal of contributing to academia. During the Ph.D. period, the candidate should focus on publishing and presenting research.

2. The candidate shall have any one of the following education backgrounds, including computer science, urban planning, transportation engineering, geographical information system (GIS), economics, statistics, or architecture/landscape design.

3. The candidate can use machine learning or statistics for mathematical modeling with the understanding of linear algebra, statistics, and machine learning.

4. The candidate needs to be familiar with Python and R.

5. The candidate is proficient in English writing and speaking.