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

 

1.  Transportation Systems Engineering: Transportation Systems Modeling, Computing, and Cloud-Based Mobility Analytics Platforms

2. Health Systems Engineering: Health Systems Data Analysis, Modeling, Computing, and Cloud-Based Health Systems Analytics and Decision Support Platforms

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

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1. Postdoctoral Associate in Transportation Systems Modeling & Urban Mobility Analytics

Center for Transportation, Environment, and Community Health (CTECH)

Cornell University – College of Engineering

Ithaca, NY

Cornell University’s Center for Transportation, Environment, and Community Health (CTECH)—a U.S. Department of Transportation Tier 1 University Transportation Research Center dedicated to advancing sustainable technology-enabled mobility for public and planetary health—invites applications for a Postdoctoral Research Associate in Transportation Systems Modeling, Computing, and Cloud-Based Mobility Analytics Platforms as part of the CTECH Postdoctoral Fellows Program.

This position offers a unique opportunity to work at the forefront of computational transportation science, AI-enabled mobility modeling, urban analytics, and cloud-based decision-support platforms for real-world transportation agencies. The Postdoctoral Associate will join a multidisciplinary team of faculty, researchers, software developers, and agency partners, and will support ongoing deployment and expansion of tools such as Cornell’s Transportation Environment Analysis Model for Cities (Cornell TEAM-Cities), the emerging urban transportation, environment, and community health modeling Hub (uTECH Hub), and the Blockchain powered Climate Actions in Transportation (CAT-Chain) ecosystems.

This position is ideal for candidates interested in research–practice integration, large-scale mobility modeling, and translating advanced systems methods into operational tools used by cities, MPOs, and state DOTs.

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Position Overview

The Postdoctoral Associate will lead and support research in:

• Transportation systems modeling and simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling
• Large-scale computing, cloud-native analytics workflows, and data engineering for mobility platforms
• AI/ML for transportation prediction, system optimization, and environmental/health impact modeling
• Deployment of decision-support tools for public-sector clients (municipalities, MPOs, DOTs)
• Urban mobility, equity, resilience, and environmental sustainability analysis
• Software engineering for cloud platforms supporting transportation planning and operations

The position includes opportunities to engage directly with city transportation departments, MPOs, state DOTs, and federal transportation agencies, contributing research that has immediate practical impact.

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Research Responsibilities

Responsibilities will vary depending on the candidate’s background, but may include:

• Developing new transportation modeling methods, including dynamic traffic assignment, AI-enhanced forecasting, optimization, or simulation-based analysis
• Building and scaling cloud-based activity-based mobility analytics systems (AWS/Azure/GCP) for large multi-city datasets
• Enhancing and deploying computational platforms such as Cornell TEAM-Cities, CATChain, uTECH, etc.
• Working with geospatial and mobility datasets (GPS trajectories, transit feeds, sensor data, demographic/socioeconomic data)
• Co-designing tools and analyses with municipal and MPO clients, including:
  • scenario modeling
  • project prioritization
  • equity assessments
  • emissions and health impact estimation
• Producing high-quality scholarly outputs including grant proposals, journal articles, conference papers, white papers, and public-facing reports
• Mentoring graduate and undergraduate researchers involved in CTECH projects

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Ideal Areas of Expertise

Applicants with experience in one or more of the following areas are especially encouraged to apply:

• Transportation Modeling & Analytics
• Agent-based or microsimulation modeling
• Multimodal network modeling (road, transit, micro-mobility, active modes)
• Travel demand forecasting or behavior modeling
• Computing & Data Systems
• Cloud computing (AWS, Azure, GCP)
• Big data pipelines, distributed computing, and geospatial data processing
• Python, R, SQL/NoSQL, containerization (Docker), Kubernetes
• API development and web-based analytics tools
• Systems, Optimization, and AI
• ML/AI for mobility prediction and optimization
• Graph algorithms, network science
• Spatiotemporal modeling
• Operational research for mobility and infrastructure
• Real-World Practice
• Prior collaboration with city/MPO/state transportation agencies
• Experience communicating modeling results to non-technical practitioners
• Familiarity with planning processes (TIP, MTP, NEPA, Vision Zero, etc.)

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Qualifications

Required:

• D. in Civil/Transportation Engineering, Systems Engineering, Computer Science, Operations Research, Urban Analytics, or related fields
• Strong expertise in transportation systems modeling and computational methods
• Demonstrated programming proficiency (e.g., Python, R, JavaScript, SQL)
• Experience working with large, real-world mobility datasets
• Ability to collaborate across disciplines and with public-sector stakeholders
• Strong oral and written communication skills

Preferred:

• Experience developing or deploying software tools used by cities or MPOs
• Cloud platform experience (AWS preferred)
• Experience with mobility platforms, APIs, or web-based dashboards
• Background in transportation–environment–public health interactions

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Application Instructions

Applicants should submit:

• CV (including names of 3 references
• Cover letter describing research interests and fit with the position
• A research statement (e.g., previous work, future research interests and directions, and career goals, etc. 3-page maximum, single space)
• Transcripts (electronic version will be fine)
• Three representative publications

To apply: Application materials can be submitted via email to hg55@cornell.edu. 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.  Inquiries can be sent to Professor H. Oliver Gao at hg55@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. Salary conforms to 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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2. Postdoctoral Associate in Health Systems Engineering

Cornell University’s Center for Transportation, Environment, and Community Health (CTECH)—a U.S. Department of Transportation Tier 1 University Transportation Research Center dedicated to advancing sustainable technology-enabled mobility for public and planetary health—invites applications for a Postdoctoral Associate in Health Systems Engineering (Health Systems Data Analysis, Modeling, Computing, and Cloud-Based Health Systems Analytics and Decision Support Platforms) as part of the CTECH Postdoctoral Fellows program.

This position offers the unique opportunity to conduct deeply interdisciplinary research spanning engineering systems, health informatics, clinical operations, data science, and decision support, contributing to the emerging research frontier of healthcare systems engineering. The Fellow will be jointly mentored by faculty from Cornell Engineering and Weill Cornell Medicine and will engage in research that advances methodological innovation while addressing real challenges in healthcare delivery.

Position Overview

The Postdoctoral Associate will contribute to research at the intersection of:

• Health systems engineering and systems architecting
• AI/ML-driven clinical and operational decision support
• Digital health and learning health systems
• Healthcare operations, resource allocation, and workflow optimization
• Network, graph, and agent-based modeling for care delivery
• Health equity, patient access, and system resilience
• Multi-modal data integration using EHR, claims, environmental, and behavioral datasets

The successful candidate will work with interdisciplinary teams of engineers, health informaticians, clinicians, data scientists, and behavioral scientists from Cornell Engineering and Weill Cornell Medicine. The role includes opportunities to collaborate with New York–Presbyterian Hospital, hospital operations teams, and partners in the digital health and health delivery ecosystem.

Research Responsibilities

Responsibilities will vary depending on the Fellow’s background, but may include:

• Developing machine learning, optimization, or simulation models to improve clinical operations and resource allocation
• Advancing systems engineering methods for health delivery design, evaluation, and transformation
• Designing and implementing agent-based, network, or graph models to study patient flow, care pathways, and population-level outcomes
• Creating data-driven and privacy-aware decision-support tools for clinicians, administrators, or patients
• Integrating multi-source, high-dimensional datasets (EHR, claims, environmental/socioeconomic data, sensor data)
• Contributing to translational research that tightens the loop between engineering innovation and clinical practice
• Disseminating findings through high-impact journals, conferences, and stakeholder engagements

The Fellow will be encouraged and mentored to establish an independent research trajectory and develop skills necessary for a future faculty or research leadership career.

Methodological Areas of Interest

Applicants with experience in the following areas are especially encouraged to apply:

• Optimization (deterministic, stochastic, robust, reinforcement learning–based)
• Systems architecting and design for complex socio-technical systems
• Graph theory, network science, and knowledge representation
• Agent-based and simulation modeling
• AI/ML, foundation models, causal inference, and predictive analytics
• Human factors, behavior science, and patient-centered design
• Advanced computing and scalable algorithms
• Decision science and learning health systems design

Qualifications

Required:

• Ph.D. in Systems Engineering, Industrial Engineering, Operations Research, Computer Science, Biomedical Informatics, Health Information Technology, or a related field
• Evidence of high-quality research productivity (publications, presentations, software, system prototypes)
• Strong analytical and computational skills (e.g., Python, R; simulation or optimization tools)
• Experience working with real-world datasets, ideally including clinical, operational, or health-related data
• Excellent communication skills and the ability to interact with multidisciplinary collaborators

Preferred:

• Research experience with EHR, claims, or clinical workflow data
• Experience with healthcare operations, health policy analysis, clinical decision support, or translational informatics
• Background in systems engineering modeling applied to human-centered or safety-critical environments
• Interest in preparing for a career as a faculty member or research leader in engineering, informatics, public health, or health systems science

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Application Instructions

Applicants should submit:

• CV (including names of 3 references
• Cover letter describing research interests and fit with the position
• A research statement (e.g., previous work, future research interests and directions, and career goals, etc. 3-page maximum, single space)
• Transcripts (electronic version will be fine)
• Three representative publications

To apply: Application materials can be submitted via email to hg55@cornell.edu. 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.  Inquiries can be sent to Professor H. Oliver Gao at hg55@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. Salary conforms to 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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3. 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 urbantechnology, digital twin and software development, infrastructure investment and asset management optimization, and infrastructure finance/policy for smart and healthy communities. Led by Professor H. Oliver Gao, a graduate field member in Civil and Environmental Engineering, Engineering Computing, Cornell Institute of Public Affairs, and Systems Engineering at Cornell University, 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 socialscientists 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 integratedsoftware 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, riskanalysis 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)

Qualification
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 inInfrastructure Policy (CPIP, http://www.human.cornell.edu/pam/cpip/), 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 aunique 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.

How to Apply:
If you are interested please contact Professor H. Oliver Gao and email your application package to: H. Oliver Gao(hg55@cornell.edu). An application prepared in English should contain:

1. A cover letter.
2. CV, include complete list of publications
3. Contact information for 3 references (can be included at the end of your CV)
4. Two or three of your publications relevant to the topic
5. A research statement (e.g., previous work, future research interests and directions, and career goals, etc. 3-page maximum, single space), and
6. A transcript (electronic version will be fine)

For convenience, please use “Post-doc application—TTP” in the subject line of your email, and name your documents as: “Your First Name_Last Name-CV”, “Your First Name_Last Name- ResearchStatement”, and “Your First Name_Last Name-Transcript”, etc.

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. Salaryconforms the Cornell University standard.

EEO/AA Policy
The College of Engineering at Cornell University is an equal-opportunity affirmative-action employer. Women and minorities are encouraged to apply.