The George Washington University, in collaboration with the NIST Professional Research Experience (PREP) program, is seeking a Postdoctoral Fellow to contribute to the NIST Smart Fire Fighting initiative. This research opportunity focuses on developing data-driven models for real-time flashover prediction in commercial buildings, aiming to reduce firefighter deaths and injuries. The project involves generating realistic fire data using CFAST Data Generation (CData), bridging fundamental fire dynamics with machine learning, and addressing challenges such as sensor failure and unknown building layouts to create robust safety tools.

Applicants should have a Ph.D. in Fire Protection Engineering, Safety Science, Civil Engineering, or related fields. Required technical skills include proficiency in CData, CFAST, FDS, and programming languages such as Python, MATLAB, or R. A strong publication record in Q1 SCI journals is expected. U.S. citizenship is preferred. The position is supervised by Professor David Broniatowski, a faculty member in Engineering Management and Systems Engineering at George Washington University.

This is an excellent opportunity for researchers interested in fire protection engineering, data science, and machine learning to make a significant impact on firefighter safety. The position is funded through the NIST PREP program, though specific funding details are not provided. Interested candidates should apply via the provided application link and ensure they meet the stated qualifications.