Post-Doc Research Opportunity in Smart and Healthy Communities

Employer
Cornell University, School of Civil and Environmental Engineering
Location
Ithaca, New York
Salary
Negotiable
Posted
Jul 20, 2021
Closes
Sep 19, 2021
Position Type
Other
Contract Type
Permanent
Organization Type
Other

Post-Doc Research Opportunity in Smart and Healthy Communities at Cornell University

Urban Technology, Digital Twin, and the Sustainability Business--Technology, Infrastructure, and Software Platform for Smart and Healthy Communities

The Cornell University Transportation and Environment/Energy Systems (CUTES) research group invites applications from outstanding researchers for a post-doctoral research position in the area of Urban Technology, Digital Twin, and the Sustainability Business--Technology, Infrastructure, and Software Platform for Smart and Healthy Communities. The successful candidate will work as part of the multi-disciplinary team of CUTES research on urban technology, digital twin and software development, infrastructure investment and asset management optimization, and infrastructure finance/policy for smart and healthy communities. The CUTES group is a cross-disciplinary research team that takes innovative systems informatics-analytics approaches to solving urban infrastructure and its associated environment/health/economics and management problems.  The CUTES research group brings together a world-class interdisciplinary team to model the whole-of-life performance of urban technology, transportation/infrastructure, and complexity of the interdependency between the built and natural environments. The research team combines social scientists with researchers in engineering and complex systems simulation: the Group involves faculty and grad/undergrad students from Civil and Environmental Engineering, Statistics, Electrical and Computer Engineering, Computer Science, Applied Economics and Management, and Systems Engineering. The CUTES Research Group has a successful history in the nexus of urban transportation and environment/energy systems research and is involved in several large-scale interdisciplinary projects in economic/environmental impact assessment such as transportation emissions and air pollution/public health in New York City. Our research seeks to combine fundamental theoretical investigations with serious applications including the modeling and development of efficient systems for extracting and processing information. We aim at developing theoretical models, hybrid numerical approaches, computational algorithms, integrated software platforms, and ultimately policy insights and practical guidelines for managing the interactions among urban technologies, infrastructure and environment networks, and consumers and communities.

Major Responsibilities

This appointment is an opportunity for a researcher with proven ability in developing complex systems analytics models, urban technology and digital twin, software and platform development, optimization methods, and computational tools for real-world problems in Urban Technology, Transportation/Infrastructure Economics, and the Sustainability Business. Experience in transportation/infrastructure economics and finance, software systems engineering, network science, information, decision and complex networks, computational and infrastructure intelligence, dynamic data driven application systems, science of information computation and fusion, or modeling multi-layer infrastructure networks is desirable. An appetite for interdisciplinary collaboration is required, and active participation in research projects and leading a group of highly motivated Ph.D. students is expected. Example research areas/activities include:

  • Data analytics, visualization and science; hybrid-models using big data and simulation models; hierarchical networks of distributed and cloud computing.
  • Mathematical and probabilistic models, hybrid numerical approaches, computational algorithms, and integrated software platforms for modeling and managing the interactions among urban technology, infrastructure networks, and users (e.g., infrastructure facility and operations management, physical asset management, maintenance and reliability analysis, infrastructure network design and planning)
  • Abstract modeling paradigms based on complex network theory and approximated network models, risk analysis methods, and a combination of simulation and advanced machine-learning techniques for Urban Technology, Transportation/Infrastructure Economics, and the Sustainability Business.
  • Performance-based engineering and economics of infrastructure system?operation and management of vital regional/urban technology, transportation, and infrastructure systems, quantification of greenhouse gas (GHG) and other pollutant emissions from infrastructure systems, impacts on economics and public health (Environmental Risk assessment and management, Resource efficiency in infrastructure systems).
  • Complex systems architectural design framework, combined with optimization models, taking into account the system of interest and its environment in modeling policy problems. Understanding of and support for the management of interdependent urban infrastructure systems, especially in the framework of life cycle management optimization. The models developed in the research will be embedded in computer-based decision aids. Such computer-based decision support is intended to assist decision makers in policy design and optimization for sustainable/resilient infrastructure and the underlying business model.
  • Revenue and Finance: Modeling and mechanism design of alternative financing options (e.g., public private partnership (PPP)) for sustainable infrastructure and environment (Infrastructure financing and business models, Life cycle cost optimization, Infrastructure supply chain management, Contract and project management, Infrastructure policy)

Qualifications

The research will be undertaken in the group of Prof. H. Oliver Gao. The appointment will be served within the School of Civil and Environmental Engineering at Cornell University in Ithaca NY, with potential interactions with other Cornell units including: Computer Science, Electrical and Computer Engineering, Atkinson Center for a Sustainable Future (ACSF, http://www.acsf.cornell.edu/), Cornell NYC Tech (http://tech.cornell.edu/), Cornell Program in Infrastructure Policy (CPIP https://www.human.cornell.edu/pam/research/cpip/home), and Cornell Institute of Public Affairs (CIPA, http://www.cipa.cornell.edu/), etc.  Applicants for this position are expected to have excellent economic modeling, data analytics and computational skills and/or hands-on experience on the modeling of urban technology, infrastructure systems and networks. We are looking for highly motivated, committed, and creative individuals, able to work in a team and with good communication skills. Working in a top-level research environment, the candidate will have a unique opportunity to develop further their research abilities.

The candidate must hold a Ph.D. degree with top performance in a field that is closely related to transportation/infrastructure networks and economics, mathematical modeling, control theory, economics and finance for complex systems. Candidates with an earned (or soon-to-be-earned) doctoral degree in Economics and finance, Civil and Environmental Engineering, Operations Research, Computer Science, or other relevant disciplines will be considered, provided their strong research track record. He or she should have a track record in conducting original highly competitive scientific research and publishing the results in top conferences and scientific journals. Maturity, self-motivation and the ability to work both independently and as a team player in local and international research teams are expected. Relevant experience could also include systems and network architecture, big data management, decentralized or distributed control. Ability to initiate new research collaborations, work in a team and be open for the application of results is important.

 

To apply: Application materials must be submitted on-line through AcademicJobsOnline at

https://academicjobsonline.org/ajo/jobs/18763

 

Through this web site, applicants are to submit a cover letter, curriculum vitae–include a complete list of publications, a research statement, 2-3 publications relevant to the topic, undergraduate and graduate transcripts and complete contact information for no fewer than three references. Questions can be directed to cee_search@cornell.edu

 Review of applications will start immediately and continue until the position is filled. Start date can be as soon as the identified candidate becomes available. Initial appointment will be for one year, with possible extensions.

 

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.

 



The candidate must hold a Ph.D. degree with top performance in a field that is closely related to transportation/infrastructure networks and economics, mathematical modeling, control theory, economics and finance for complex systems. Candidates with an earned (or soon-to-be-earned) doctoral degree in Economics and finance, Civil and Environmental Engineering, Operations Research, Computer Science, or other relevant disciplines will be considered, provided their strong research track record. He or she should have a track record in conducting original highly competitive scientific research and publishing the results in top conferences and scientific journals. Maturity, self-motivation and the ability to work both independently and as a team player in local and international research teams are expected. Relevant experience could also include systems and network architecture, big data management, decentralized or distributed control. Ability to initiate new research collaborations, work in a team and be open for the application of results is important.