Internship, Master's Thesis, Semester Project — AI for Physics & Engineering Simulations

Description

We are launching an exciting new research initiative at IBM Research to leverage AI for developing novel algorithms that accelerate computer simulations of complex physical and engineering systems. Many natural and engineered phenomena are governed by complex differential equations. Traditional solvers require significant domain expertise and require expensive resources. AI-driven methods are changing this paradigm. By learning the underlying physics from simulation data, AI can build surrogate models that deliver high-fidelity results in seconds, enabling faster innovation across science and engineering.

As a student in our team, you will have the opportunity to contribute to this cutting-edge research, tackling problems that span:

• Fluid dynamics
• Solid mechanics
• Fluid-Structure Interaction
• Heat transfer
• Friction and contact mechanics
• Chemistry and materials science
• Coupled multi-physics systems

We now have plenty of ideas on how to bring this work to the next level, and we can offer research and innovation projects on topics such as:

• Algorithm development
• Scalability, parallelization, and computational efficiency
• Geometry and mesh optimization
• Foundation models for ODEs and PDEs
• Inverse modeling

Why Join Us?

A unique aspect of our projects is the chance to work with real-world, client-provided datasets that are not publicly available. These datasets present challenges that often push beyond the limits of today’s most advanced AI methods, making them an excellent opportunity for impactful innovation. As part of our team, you will collaborate closely with experienced Research Scientists and AI Software Engineers who will guide you through ambitious research tasks and help you succeed. Also, you will have the opportunity to work with our academic and industrial partners. In addition, you will have access to modern GPUs and cloud infrastructure to accelerate your work.

We actively encourage interns to file their first patent with us and to publish in top AI conferences — giving you a strong foundation for both academic and industry careers.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Machine Learning, or a related technical field (or equivalent practical experience)
• Strong programming skills
• Proficiency with Unix/Linux environments
• Excellent communication and presentation skills in English
• Team-oriented, self-motivated, and able to solve problems independently

Preferred Qualifications

• Experience with one or more of the following:
  • Physics-Informed Neural Networks (PINNs)
  • Neural Operators / Neural Solvers
  • Algorithm development
  • Distributed computing, data structures, test automation, or CI/CD
• Hands-on experience with PyTorch
• Advanced programming skills (e.g., C/C++ or CUDA)
• Ability to work independently and adapt in a fast-paced, evolving research environment

References & Further Reading

• IBM Research is turbocharging algorithm development for a world with quantum computing and AI
• Neural operators as a PDE solution paradigm: https://arxiv.org/abs/2108.08481
• Breakthrough approach in the car domain: https://arxiv.org/abs/2309.00583
• Recent SOTA work on Neural Operators: Transolver GitHub and Arxiv article

How to apply

Please submit your CV including contact information for two or three references. We encourage candidates to also share a 3-minute video, in which they introduce themselves, as well as highlight their motivation and expertise. The video is not mandatory.

Interview process

After the initial screening based on the uploaded documentation, identified candidates will be contacted for a first technical discussion on their experience, background, and motivations, followed by a coding interview and a project matching discussion. If you have any question related to this position, please contact Dr. Cezar Zota, zot@zurich.ibm.com .