Research Engineer Computer Graphics & Physically- Simulation

Research Engineer Computer Graphics & Physically-Based Simulation

We are seeking a talented Research Engineer with strong expertise in Computer Graphics, physically-based simulation, and high-performance implementation. In this role, you will design, prototype, and optimize advanced simulation algorithms—particularly in the domain of cloth and deformable materials—and contribute to our next generation of rendering and learning-based graphics technologies. You will collaborate closely with other research scientists and engineers to transform cutting-edge research into robust, production-quality systems.

We are looking to fill this role as part of an Innosuisse project where ETH is the research partner alongside implementation partner Vestir AI. In this project we are working on revolutionizing online fashion shopping through the use of advanced 3D Computer Vision and Computer Graphics techniques to digitize human avatars and garments in 3D. Within this project, your role is to implement physically-based garment simulation techniques and work on efficient rendering algorithms.

• Develop and optimize physically-based simulation algorithms, with a focus on cloth, soft bodies, or deformable materials.
• Implement high-performance C++ and Python modules for simulation, rendering, and data processing.
• Explore and integrate deep learning techniques into graphics and simulation pipelines (e.g., PyTorch, JAX, Tensor Flow).
• Build tools for debugging, visualization, and validation of simulation results.
• Contribute to research and prototyping in real-time graphics, differentiable simulation, or novel rendering techniques, such as Gaussian Splatting.
• Collaborate with other team members to transition research prototypes into production-ready features.
• Stay current with the latest academic and industry advances in physics simulation, rendering, and neural graphics.

• Bachelor’s, Master’s, or PhD in Computer Science, Computer Graphics, or a related field.
• Strong proficiency in C++ and Python, with a track record of building performant, maintainable software.
• Hands-on experience with physically-based simulation, particularly cloth, deformable solids, or mass-spring/finite-element methods.
• Strong understanding of computer graphics fundamentals, numerical methods, and GPU/parallel computing concepts.
• Experience with at least one major deep learning framework (PyTorch preferred).
• Excellent problem-solving skills and the ability to independently drive projects from concept to completion.

Bonus

Qualifications:

• Experience with Gaussian Splatting.
• Familiarity with CUDA, compute shaders, or other GPU programming environments.
• Experience with differentiable simulation or inverse problems in graphics.
• Publications in top-tier graphics or ML venues (SIGGRAPH, CVPR, ICCV, NeurIPS, etc.) are a plus but not required.

• A stimulating academic environment at one of the world's leading technical universities.
• The opportunity to transform research into a product that will disrupt the fashion industry with global impact.
• Being a part of a coreteam working at the forefront of scientific innovation.
• Flexible working arrangements, including options for remote work.

In line with our values , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Sustainability is a core value for us – we are consistently working towards a climate-neutral future .

We look forward to receiving your online application with the following documents:

• CV/Resume
• Cover letter explaining your interest and qualifications
• Contact information for 2-3 references

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about the ETH AI Center can be found on our website . Questions regarding the position should be directed to Dr. Manuel Kaufmann, manuel.kaufmannz.ch (no applications).

Pre-selection is carried out by the responsible recruiters and not by artificial intelligence.