Scientific AI Research Intern-CR

 About the Role

We are looking for motivated interns interested in scientific AI research. In this internship, you will contribute to the development of next-generation numerical simulation frameworks powered by artificial intelligence. You will have the opportunity to apply machine learning techniques to accelerate, enhance, and rethink scientific simulations.

Depending on your background, you may:

• Design AI-driven models for physical systems

• Integrate data-driven methods with classical simulation approaches

• Explore novel architectures for differentiable simulation and scientific computing

This role is well-suited for students passionate about combining numerical modeling with modern AI techniques to advance the frontiers of computational science.

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As an intern, you will:

• Participate in the development of AI-assisted numerical simulation frameworks

• Implement and test AI models for scientific computing tasks

• Analyze simulation results and validate them against theoretical or experimental data

• Document methods, experiments, and findings in a clear and reproducible way

• Collaborate with researchers and engineers to explore and refine new ideas

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We welcome candidates with strengths in either scientific AI or numerical methods (you do not need expertise in both).

• Currently pursuing a degree in Applied Mathematics, Physics, Engineering, or a related discipline

• Solid programming skills in Python or C++

• Familiarity with at least one of the following areas:

o Machine learning frameworks (e.g., PyTorch, JAX, TensorFlow)

o Numerical methods or simulation techniques (e.g., PDE solvers, DEM, MPM, MPS)

• Strong analytical and problem-solving skills

• Curiosity, adaptability, and eagerness to learn new concepts

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