Anticipated Start Date: ASAP
Location: Flexible (relocation not required)
Position Summary: The School of Industrial Engineering and Lyles School of Civil Engineering at Purdue University are seeking a Postdoctoral Research Associate for a project, sponsored by the Louisiana Office of Community Development and US Department of Housing and Urban Development. The postdoc will work to develop a statewide inventory of structures and associated structural attributes relevant to flood risk vulnerability (e.g., first-floor elevations, number of stories). The research focus of the project is to advance existing methods applying artificial intelligence (including deep learning and computer vision) to Google Street View imagery in order to identify the structural attributes in an automated, scalable manner. The postdoc will work with an interdisciplinary group of faculty at Purdue University and research staff at The Water Institute of the Gulf.
The position includes an initial appointment through end of August 2021, with the possibility for renewal pending additional funding expanding the project to other Gulf Coast states.
Duties and Responsibilities (100% time):
- Develop novel data fusion techniques and deep learning approaches to image analysis for feature extraction
- Merging and resolving conflicts between multiple structure- and parcel-level inventory data sets (e.g., Google Street View, Microsoft Building Footprints, National Structure Inventory, CoreLogic, ATTOM Data Solutions)
- Assist in supervision and mentorship of graduate and undergraduate research assistant(s)
- Actively publish results of the research in appropriate peer-reviews journals or conference proceedings
A successful applicant will have
- PhD in relevant area with associated peer-reviewed publications
- Proficiency in relevant languages for scientific computing (e.g., R, Python)
- Experience with GIS analysis, computer vision, machine learning and deep learning
- Strong organizational skills and experience with data management for large projects
Additional preferred qualifications include:
- Familiarity with related topical concepts such as risk analysis, flooding, and/or structural engineering