Postdoctoral Research Statistics of Infrastructure Management
- Employer
- Air Force Institute of Technology, Engineering Management Program
- Location
- Dayton, Ohio
- Salary
- $70,000+ per year including a stipend for health insurance and moving expenses
- Closing date
- Jan 19, 2023
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- Specialty
- Structural Engineering, Utility Engineering, Water Resources Engineering
- Position Type
- Postdoc
- Contract Type
- Contract
- Organization Type
- Academia
Job Details
Dr. Christopher Chini and faculty at the Air Force Institute of Technology are hiring one or two postdoctoral researchers across multiple different infrastructure management projects. Postdoctoral researchers will work with Dr. Christopher Chini and collaborators on joint research projects related to applied statistics of infrastructure systems. We will begin reviewing applications on January 3, 2023. Anticipated Appointment Start Date: as soon as possible. Postdoctoral research positions are for up to two years with the potential for a one-year extension contingent upon performance and funding. Starting salary is $70,000+ per year including a stipend for health insurance and moving expenses. Note: postdoctoral researchers will be contractors to the federal government and employment carries no military commitment.
Data management and statistical applications for decision-making of infrastructure are increasingly becoming important in civil engineering. The following three projects each offer opportunities to advance infrastructure management through statistical approaches.
1. Topic: Statistical approaches for Structural Health Monitoring. The project will look at multiple gyroscopic and strain sensors that have been placed on the frame of an aircraft hangar in Florida. These sensors have high resolution and can be paired with an on-site anemometer. Using appropriate statistical techniques, the research will characterize change points, control states for failure, and compare against a built structural model to develop insights associated with future building performance modeling.
Candidate Requirements: Experience in statistical programming methods including Bayesian statistics is a benefit.
2. Topic: Statistical deterioration modeling of water and electricity infrastructure. The project will utilize cross sectional data of a large number of water and electric utilities to categorize deterioration of assets. Statistical methods include Markov Chain Monte Carlo and/or machine learning techniques to identify how infrastructure might age. Additionally, the research will investigate the level of investment needed to maintain or improve the overall infrastructure health through time.
Candidate Requirements: Experience in statistical programming methods including Bayesian statistics is a benefit.
3. Topic: Statistical methods for understanding drought and heat wave impacts on electric grid transfers. The research will utilize a time series of electricity exchanges between balancing authorities in the United States. Utilizing a number of independent variables, the research will characterize how droughts and heat waves impact the magnitude of electricity trade between balancing authorities. These insights can be extrapolated using downscaled climate data to understand how more frequent regional climate events can impact reliability of neighboring balancing authorities and, therefore, overall reliability.
Candidate Requirements: Experience with machine learning techniques in any language. Previous experience with research regarding the energy-water nexus is a benefit.
4. Topic: Resilience and Recovery Modeling of Coastal Infrastructure to Hurricanes. The project will investigate coastal infrastructure, particularly the electric grid of Florida, and simulate hurricane damage through fragility assessments. The research will then identify critical infrastructure impacted through failings of the power grid, recovery scenarios, and resilience adaptation measures.
Candidate Requirements: Experience with geospatial information systems and infrastructure modeling. Previous experience with the electric grid is a plus, but not required.
All postdoctoral positions will be administered through the U.S. Department of Energy (DOE) and Oak Ridge Institute for Science and Education (ORISE), established through an interagency agreement between DOE and DOD. The participant will receive a monthly stipend commensurate with educational level and experience, as well as coverage (100% of total premium) of individual health insurance, available through ORISE. A relocation stipend will also be provided. Proof of health insurance is required for participation in this program. The appointment is full-time at AFIT in Dayton, OH. Participants do not become employees of the DOD, DOE or the program administrator, and there are no employment-related benefits.
To apply for the position, contact Dr. Christopher Chini at christopher.chini.1@au.af.edu. Provide a curriculum vitae and examples of up to 3 previous publications. Position is open until filled.
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