Phd Research Intern
Robotic Perception, Summer 2024
Confirmed live in the last 24 hours
NVIDIA

10,001+ employees

Designer & manufacturer of computer chips & graphics processors
Company Overview
NVIDIA is on a mission to solve the world's most stimulating technology problems – in industries ranging from gaming to scientific exploration.
AI & Machine Learning

Company Stage

N/A

Total Funding

$4.2B

Founded

1993

Headquarters

Santa Clara, California

Growth & Insights
Headcount

6 month growth

6%

1 year growth

0%

2 year growth

15%
Locations
Remote in USA • Redmond, WA, USA • Santa Clara, CA, USA
Experience Level
Intern
Desired Skills
Python
Communications
CUDA
Data Structures & Algorithms
Pytorch
Computer Vision
CategoriesNew
Lab & Research
AI & Machine Learning
Requirements
  • Pursuing a Ph.D. in Computer Science/Engineering, Electrical Engineering, etc.
  • Excellent knowledge of theory and practice of computer vision methods, as well as deep learning.
  • Expertise in one of more of the following areas: computer vision, object pose estimation, 3D reconstruction, end-to-end learning of perception & controls, object affordance, sim-to-real learning of robotic policies, robotic manipulation
  • Excellent programming skills in some rapid prototyping environment such as Python. C++ and parallel programming (e.g., CUDA) is a plus.
  • Knowledge of common machine learning frameworks, such as PyTorch.
  • Proven track record of publication in top-tier conferences.
  • Excellent communications and analytical skills.
Responsibilities
  • Reproduce existing state-of-the-art computer vision methods
  • Research, design, and implement novel deep learning algorithms to push the state of the art in computer vision
  • Publish original research
  • Collaborate with other team members, research teams, as well as product teams
  • Transfer technology to product groups
Desired Qualifications
  • C++ and parallel programming (e.g., CUDA) experience
  • Experience with rapid prototyping in Python
  • Familiarity with machine learning frameworks such as PyTorch