We propose a holistic and inclusive research and training program to the Department of Energy’s Reaching a New Energy Sciences Workforce initiative (DOE RENEW) to provide students and early career scientists with opportunities to gain in-depth experience in understanding extreme natural hazards and solving the associated and expanding societal challenges caused by these events. The project aims to improve the knowledge of extreme natural hazards by quantifying and understanding the properties of floods, landslides, heatwaves, and multi-hazard impacts in the Greater New York metropolitan area. A synergistic approach that blends Artificial Intelligence and Machine Learning with traditional computational methods will be used to create more robust, scalable, and dynamic climate-informed natural hazard risk management tools for the next generation of energy science workforce. The project intends to prepare and promote well-trained, diverse graduates and postdoctoral scientists who will become part of the next generation in government, industry, and academia. The trainees will gain the skillsets necessary to immediately contribute to ongoing resilience and adaptation projects in a cost and schedule-driven environment and an increasingly AI-driven workplace. The project brings together a team of multidisciplinary researchers, including civil, environmental, and electrical engineering, climate, atmospheric, and ecosystem science, data science, as well as education and workforce training specialists. The team will work together to prepare a hazards-ready workforce in the Greater New York metropolitan area, one of the densest urban regions in the country and home to nearly 25 million people.