Internship - Research (Uncertainty Quantification, Robust Design & Surrogate Modeling)

About the role#

We are seeking a Research Intern to contribute to exploratory research projects focused on uncertainty quantification, experimental design, robust design methodologies, and surrogate modeling. This role supports the development of methodological foundations for scientific and engineering applications. Projects will be structured to provide clear research value, with specific focus areas shaped by the intern's background and strengths.

What you'll do#

• Conduct exploratory research to improve and extend uncertainty quantification methodologies.
• Support the development of experimental and robust design approaches for scientific and engineering tasks.
• Develop or evaluate surrogate modeling approaches for complex systems.
• Collaborate with researchers to define and execute meaningful, isolated research projects.

What you'll need#

• Currently pursuing a Master’s or PhD in Applied Mathematics, Computer Science, Physics, or a related field.
• Strong proficiency in Python.
• Solid background in probabilistic machine learning, uncertainty quantification, or Bayesian computation.
• Strong mathematical and analytical skills.
• Ability to work independently on technically demanding research tasks.

Location & details#

• Term: Summer 2026.
• Location: Boston, Massachusetts.
• Work Modality: Hybrid (4 days on-site, 1 day remote).
• Status: Paid, full-time internship.