PhD Research Intern, Cross-Disciplinary Vision Science - Summer 2027

NVIDIA

Santa Clara, CA, United States1w ago

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Key details

Location
Santa Clara, CA, United States
Work style
Onsite
Level
Intern
Job type
Full-time
Function
other
Focus area
other
Posted
1w ago

Skills

c++computer visioncontrol systemsdeep learninggitllmpythonpytorchrust

About the role

NVIDIA has been transforming computer graphics and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAn, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.


We, the Human Performance and Experience (HPX) team at NVIDIA Research, strive to lead AI innovation by deeply understanding humans. We are looking for individuals who are passionate about cross-disciplinary research in vision between humans and machines. We expect candidates with backgrounds in computer vision, human vision science, robotic vision, and related fields to be well-suited to this position. You will be working in a team of research scientists and engineers from varied backgrounds and closely collaborating with product engineers. Join us in transforming the future of AI and human interaction.


What you’ll be doing:

  • Decompose research questions into smaller, more manageable parts and tackle them in iterative steps.
  • Think critically to identify unseen gaps, and creatively bridge them with non-traditional, high-impact solutions.
  • Connect with researchers and product engineers to ground research findings in real-world problems.
  • Lead knowledge dissemination effort, with options for conference, journal, and in-house publication.

What we need to see:

  • Currently pursuing a Ph.D. or equivalent academic program, demonstrated by a track record of research and publications.
  • Deep interest in gaming and/or human behavior in related application domains.
  • Training or systematic knowledge and skill in the field of Cognitive Science, Neuroscience, Computer Science/Engineering, Electrical Engineering, or related fields.
  • Proficiency with Python, Rust, and/or C++.
  • Experience with AI model training and evaluation frameworks, like PyTorch.

Ways to stand out from the crowd:

  • Experience with quantitatively modeling human perception, cognition, movement, and/or decision-making.
  • Comfortable with modern software development, version-control systems, like git(hub/lab). 
  • Experience with multi-node, multi-GPU training and inference workflows.
  • Familiarity with and interest in modern deep learning models, including working with large-scale, multi-modal foundation models (such as recent LLMs, VLMs).
  • Demonstrated public portfolio (e.g. repositories, OSS contributions, notebooks, packages, or technical blog posts with code).

Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 38 USD - 94 USD.

You will also be eligible for Intern benefits. ​

Applications for this job will be accepted at least until October 10, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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