Math Libraries Intern, cuEST - Summer 2027

Responsibilities

• Prototype and develop GPU-accelerated algorithms for Gaussian-basis quantum chemistry primitives in cuEST.
• Analyze the performance of CUDA implementations, identify opportunities for improvement, and implement them.
• Contribute across the engineering lifecycle, from design and testing to code that ships in the library.
• Collaborate with team members and other stakeholders to understand how quantum chemistry applications use cuEST and what they need from it.
• What we need to see
• Pursuing a BS, MS, or PhD degree in Computational Chemistry, Computational Physics, Computer Science, Applied Math, or an equivalent program area.
• Excellent C/C++ or Python programming, debugging, performance analysis, and test design skills.
• Strong algorithms and numerical methods fundamentals.
• Ability to work independently and lead your own development effort.
• Good teamwork, communication, and documentation habits.

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