Applied Mathematician Intern

Boeing

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Quick summary

Work type
On-site
Location
North Charleston, SC
Employment
Intern
Posted
3 days ago
Freshness
Confirmed live yesterday
Closes
Oct 9, 2026

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Salary context

How this pay compares to similar roles

Similar $182k
$132k most similar roles pay here $232k

This listing doesn't post a salary. Most similar roles pay $141,875–$222,750.

Based on 240 similar postings.

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About Boeing

Boeing is the world''s largest aerospace company and leading manufacturer of commercial jetliners, military aircraft, defense systems, and space launch vehicles for customers in 150 countries. Industry: Aerospace & Defense Manufacturing

Boeing currently has 39 open roles on FindRole.

Listed pay typically runs $118,150–$159,850 across 34 roles with salary data.

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At a glance

TL;DR · Applied Mathematician Intern

The Boeing Engineering & Technology Innovation Graduate Researcher Program, Applied Mathematician Intern role is situated within the Applied Mathematics group of the Engineering & Technology Innovation team. This position involves developing novel mathematical solutions, contributing to research proposals, and translating technical insights into impactful models, software, and decision-making tools for aerospace systems. The intern will work on advanced research, algorithm development, and technical consulting using methods such as geometry optimization, computational modeling, machine learning, and statistical analysis. Required skills include a strong background in statistics, numerical methods, and data analytics, alongside proficiency in programming languages like Python, R, or C/C++. Candidates may also utilize tools such as NumPy, SciPy, PyTorch, or TensorFlow. The role addresses complex aerospace challenges to create safer, more efficient systems by applying mathematical techniques to real-world engineering problems.

What you'll do

  • Develop novel mathematical solutions to solve complex aerospace challenges.
  • Translate theoretical concepts into robust algorithmic implementations for engineering systems.
  • Apply advanced methods like geometry optimization, computational modeling, and machine learning to technical problems.
  • Conduct statistical analysis and uncertainty quantification for aerospace data.
  • Build predictive models and simulations using real-world aerospace datasets.
  • Develop software and decision-making tools based on technical insights.
  • Contribute to the creation of research proposals within the Applied Mathematics group.

What we're looking for

  • Must have completed the first year of PhD studies by July 2027.
  • Pursuing a PhD in Applied Mathematics, Statistics, Computational Science, Engineering, Data Science, Machine Learning, or a related field.
  • Ability to work full-time for 10-12 weeks during Summer 2027.
  • Strong background in statistics, numerical methods, and data analytics with the ability to apply mathematical methods to real-world problems.
  • Experience designing and analyzing experiments or simulations, including uncertainty quantification and probabilistic modeling.
  • Proficiency in programming for data analysis and scientific computing using Python, R, or C/C++.
  • Must be a U.S. Person as defined by 22 C.F.R. §120.62 to meet export control requirements.
  • Security Clearance.

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