Structural Engineering Internship; Catastrophe Modeling PhD/Graduate Student
Listed on 2026-07-01
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Engineering
Research Scientist -
Research/Development
Research Scientist, Data Scientist
Structural Engineering Internship (Catastrophe Modeling) - 2026 (PhD / Graduate Student)
Karen Clark & Company (KCC) is seeking a qualified candidate for a 2026 internship with a term of at least 8 weeks. The selected candidate will work with the Model Development Team in-person in KCC's Boston office to support the development of advanced catastrophe reference models. In this position, you will work closely with other scientists and engineers to develop and manage the vulnerability module of KCC's catastrophe models.
The internship is supervised by senior staff and provides hands-on experience working on real-world science and engineering problems in the catastrophe modeling industry.
Expected Pay: $25 per hour
About KCC
Karen Clark & Company (KCC) is the innovation and technology leader in weather, climate, and catastrophe risk modeling. KCC professionals are globally recognized experts in catastrophe modeling and risk management. From our headquarters in Boston, Massachusetts, we provide advanced models, innovative software, and comprehensive consulting services to (re) insurance company executives nationwide. These services enhance business strategies, and the financial results put our clients at a competitive advantage.
KCC catastrophe models currently cover tropical cyclones, extratropical cyclones, severe convective storms, floods, earthquakes, winter storms, and wildfires in over 50 countries.
Qualifications
- MS or PhD candidate in Structural Engineering, Civil Engineering, or a related field with focus on natural hazards (e.g., wind, flood, wildfire, earthquake)
- Understanding of structural behavior and damage mechanisms under natural hazards
- Familiarity with probabilistic methods and basic risk modeling concepts
- Experience with numerical modeling or simulation (e.g., structural analysis, fragility/vulnerability modeling)
- Proficiency in Python or similar language for data analysis; ability to work with and process large datasets
- Strong analytical and problem-solving skills, with attention to detail
- Clear technical communication skills (written and verbal)
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