The College of Engineering at Cornell University is searching for highly motivated postdoctoral research candidates interested in the general research area of analysis and optimization of networked transportation systems. The position will be part of an interdisciplinary research initiative that spans the Civil Engineering (Transportation), Operations Research, and Applied Mathematics programs at Cornell University.
Project summary: The high level goal of the project is to study the emergent behavior in integrated multi-modal transportation systems where on-demand mobility services operate seamlessly with both each other and mass transit systems. An integrated system of this nature has the potential to greatly improve the efficiency and scalability of urban transportation, while concurrently reducing negative externalities such as congestion and pollution. We are interested in studying problems related to vehicle routing, integrated fleet management, pricing and incentive mechanisms, and transit network design amongst others. The project will involve close partnerships with multiple private and public sector organizations in this space.
Job description: The postdoc will be part of a team working on the analysis and optimization of integrated on-demand transit systems. Being part of a cross departmental group, the postdoc will have the opportunity to interact with faculty members and students from multiple research groups at Cornell. The postdoc will be expected to carve out his/her own research problems within the scope of the project in collaboration with the PI's. The contributions are expected to be both theoretical and practical in nature, developing new methodologies and implementing them using real-world data from our industry collaborators. Successful candidates are expected to publish in top-tier journals and conferences in collaboration with faculty and students.
Required background: We are looking for a creative and talented scientist with a good publication record and excellent organizational and communication skills. The ideal candidate will have a PhD in operations research, computer science, applied mathematics, civil engineering or a related field, with a strong background in either discrete optimization, algorithms, stochastic processes, control theory or data-driven optimization. The candidate is also expected to have experience with some high level programming language (e.g. Python). Finally, he or she must have an interest in both the theoretical aspects of networked transportation systems and the practical challenges of implementing this theory in the real-world.
To apply: Application materials must be submitted online at https://academicjobsonline.org/ajo/jobs/17792 Through this website, applicants are required to submit (1) a curriculum vita, (2) short research statement, (3) copies of two most significant research articles and 4) contact information for three references. For further information, contact Samitha Samaranayake (firstname.lastname@example.org) and Siddhartha Banerjee (email@example.com).
Review of applications will start immediately and continue until the position is filled. Start date can be as soon as Spring 2020, but is flexible. Initial appointment will be for one year, with possible extensions. Salary conforms with the Cornell University standard.
The School of Civil and Environmental Engineering and the College of Engineering at Cornell embrace diversity and seek candidates who can contribute to a welcoming climate for students of all races and genders. Diversity and inclusion are a part of Cornell University's heritage. We are a recognized employer and educator valuing AA/EEO, Protected Veterans, and Individuals with Disabilities.
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Diversity and Inclusion are a part of Cornell University's heritage. We are a recognized employer and educator valuing AA/EEO, Protected Veterans and Individuals with Disabilities. We also recognize a lawful preference in employment practices for Native Americans living on or near Indian reservations. Cornell University is an innovative Ivy League university and a great place to work. Our inclusive community of scholars, students, and staff impart an uncommon sense of larger purpose, and contribute creative ideas to further the university's mission of teaching, discovery, and engagement.
Internal Number: JOB_POSTING-3-34734
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