Assistant Professional Researcher - Shared Mobility Services and Travel Behavior

The 3R Future Mobility (3RFM) in the Institute of Transportation Studies (ITS) is in search of a new hire of Assistant Professional Researcher to lead an independent and collaborative research program examining the adoption and frequency of use of new shared mobility services, their impacts on travel demand and behavior, and associated policy implications. This includes simulating behavioral changes in large-scale travel demand models and evaluating related transportation policy issues.

This position will be housed within the 3 Revolutions Future Mobility (3RFM) Program at the UC Davis Institute of Transportation Studies (ITS-Davis) and will focus on investigating disruptive trends in the transportation sector, particularly those related to the emergence of shared mobility services, vehicle automation, and electrification.

The candidate will coordinate with Dr. Giovanni Circella, Director of the 3RFM Program, Dr. Yongsung Lee, Co-Director of the 3RFM Program, and ITS Director at UC Davis, to assist with the overall strategic research scope in the area of future of mobility studies and research projects also in cooperation with other UC campuses and partner institutions. This includes developing innovative and policy relevant research questions, identifying potential funding sources and securing them, organizing and leading scientific studies, and supervising postdoctoral researchers and graduate students participating in related projects addressing the linkages among the adoption of new transportation technologies, such as shared mobility, connected and automated vehicles, and advanced air mobility, and broader factors including land use and transportation, modifications in urban growth patterns, changes in travel behavior across different population groups, and policies to promote decarbonization, sustainable mobility, and resilience.

Skills required for this position include extensive experience with travel behavior research; the development and application of travel survey methods for the collection of travel behavior and attitudinal data; the use of quantitative methodologies, such as multivariate statistical analysis methods and the estimation of (a) econometric, (b) structural equation, (c) discrete choice, and (d) latent class models; experience with qualitative research methods such as interviews, focus groups, and content analysis, and the ability to apply and interpret outputs from advanced travel demand forecasting models and evaluate the effectiveness of transportation and land use policies. Additional desirable, but not required, skills would include the ability to conduct big data analysis and apply machine/deep learning techniques for travel behavior analysis.

Unit: https://its.ucdavis.edu/research/

* Ph.D. in science, engineering, public policy, urban planning, transportation, or a related field, with at least three years of postdoctoral or equivalent research experience.

* Demonstrated record of peer-reviewed publications and policy-relevant research outputs like project reports or policy briefs.

* Proven expertise in designing and administering transportation surveys, conducting behavioral experiments, and applying quantitative data analysis, including econometric, structural equation, discrete choice, and latent class models.

* Proven expertise in designing and conducting qualitative studies, such as facilitating interviews and focus groups, and performing content analysis.

* Experience managing confidential data in compliance with IRB requirements.

* Proficiency in statistical and programming tools such as R, Stata, Mplus, and/or Python.

* Demonstrated ability to secure internal and external research funding and manage projects from inception through completion.

* Experience supervising graduate students and mentoring undergraduate researchers.

* Strong interpersonal, collaboration, and networking skills with diverse stakeholders, including state agencies, local governments, and industry sponsors.

* Proficiency in GIS software and experience with large-scale, high-resolution mobility datasets (e.g., anonymized cellphone or GPS data).

* Experience working on interdisciplinary, multi-campus, and international collaborations.

* Knowledge and working experience related to emerging transportation technologies, including but not limited to shared micromobility, connected and automated vehicles, and advanced air mobility.

* Knowledge of machine learning and deep learning methods for travel behavior or policy analysis.

* Evidence of science communication to technical and non-technical audiences (e.g., briefings, workshops, policy reports).

* Familiarity with Latent GOLD and/or Julia or a demonstrated ability to quickly learn new analytical tools.

• 3-7 required (contact information only)

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