FM is a leading property insurer of the world's largest businesses, providing more than one-third of FORTUNE 1000-size companies with engineering-based risk management and property insurance solutions. FM helps clients maintain continuity in their business operations by drawing upon state-of-the-art loss-prevention engineering and research; risk management skills and support services; tailored risk transfer capabilities; and superior financial strength. To do so, we rely on a dynamic, culturally diverse group of employees, working in more than 100 countries, in a variety of challenging roles. Our Research team is seeking a graduate student or advanced undergraduate student in computational science or related fields (e.g. applied mathematics, computer science, mechanical engineering, etc.) to join a team of scientists dedicated to computational modeling of fire dynamics as a summer intern. The project involves developing algorithms and applying scientific machine learning approaches in numerical heat transfer and fluid dynamics problems. Responsibilities: 1. Support a project in the area of scientific machine learning and radiative heat transfer. 2. Develop, integrate, and implement algorithms to address computational issues in combustion and fire scenarios. 3. Present the research outcomes in project meetings and prepare deliverable reports and journal publications. Doctorate preferred, graduate student or advanced undergraduate student in computational science or related fields (e.g. applied mathematics, computer science, mechanical engineering, etc.) 1. Demonstrated ability to reduce theoretical knowledge and algorithm to practical applications and produce high-quality research results. 2. Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, JAX) and familiarity with recent research trends in AI for Science and scientific machine learning (e.g., physics-informed neural networks and operator learning). 3. Prior experience developing scientific computing code, computational fluid dynamics code and familiarity with fire protection engineering concept are a plus. 4. Strong analytical, problem-solving, and communication skills This is an in-office role based in Norwood, MA. Temporary relocation support provided for selected qualified candidate. FM is an Equal Opportunity Employer and is committed to attracting, developing, and retaining a diverse workforce. **\#LI-TA1**