Transportation Technology and Policy (TTP) is an interdisciplinary Graduate Group administered through the Institute of Transportation Studies (ITS). It offers three degrees: MS Plan I, MS Plan II, and Ph.D. The TTP program provides an opportunity to do interdisciplinary research to address pressing transportation, environmental, economic, policy and social challenges facing California, the United States, and the world with students coming from a variety of disciplines to pursue either a technology or policy track.
The TTP graduate curriculum draws on a multitude of academic disciplines and the group utilizes participating faculty or temporary faculty to staff courses to maintain a top-quality academic program. The following describes our search procedures and selection process for re-appointment or for hiring new temporary faculty.
Criteria for appointment and reappointment will be evidence of teaching excellence (or, for first-time, relatively inexperienced candidates, the potential for excellence) in terms of (1) rigorous and intellectually challenging course content and (2) the ability to present that material effectively, e.g., stimulating interest in and critical thought regarding the subject matter. Whenever possible, candidates holding an earned doctorate will be preferred; however, a master's degree and prior professional success and recognition for excellence will be weighted heavily and considered as minimum requirements.
Expertise in the subject matter will be evaluated based on the candidates’ academic training, publications, professional recommendations, and prior achievement (student ratings, etc.) in teaching. Course content will be evaluated on the basis of course syllabi, and choice of readings. Quality of presentation will be assessed on the basis of student evaluations.
Courses Open for Recruitment, Academic Year 2018-2019:
- “Applied Data Analysis” - This course aims to provide students with the resources needed to examine, parse, and analyze datasets (with a specific aim for answering research questions). This data analysis course covers a variety of concepts across disciplines of economics, statistics, and machine learning but with a specific emphasis on application. All techniques will be taught through practical examples of real-world datasets with enough breadth to understand the most critical concepts behind various analysis techniques.
- “Energy and Transportation Modeling for Policy Analysis” - The course will familiarize students with building energy models for policy analysis, with an emphasis on the Transportation sector. Energy systems modeling covers a wide gamut of energy sectors and some of the most important elements (transportation, electricity, fuels, resources, infrastructure) will be reviewed in the course. The primary aim of the course will be on understanding the elements and techniques for modeling transportation
- “Travel Behavior Theories” - draw on economics, psychology and sociology to provide a foundation for research in individual behavior and decision-making. Behavior theories aim to identify and describe the factors and processes including psychology, self-efficacy, attitudes, goals, and environmental and social factors, important in behavioral outcomes. This course examines theories of behavior and their application to understanding travel behavior, focusing on policy applications. Theories of individual behavior include the rational choice model, utility maximization, heuristics, planned behavior, social networks, stages of change, and others. The fundamental assumptions, model of the individual, decision-making processes, and key characteristics of the choice environment for each theory are covered. Coursework includes application of theories to travel behavior outcomes of interest, with particular attention to the implications for policy and planning. See http://catalog.ucdavis.edu/programs/TTP/TTPcourses.html for course descriptions.
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