Research Intern – Video Action Segmentation & Continual Learning - Honda Research Institute USA

Research Intern – Video Action Segmentation & Continual Learning

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Research Intern – Video Action Segmentation & Continual Learning

Job Number: P24INT-47
Honda Research Institute USA (HRI-US) is seeking a highly motivated and independent PhD research intern to join our team in advancing the frontiers of human action understanding and computer vision in long procedural videos. The project focuses on action segmentation and continual learning, particularly under conditions where new tasks and action classes are introduced incrementally without forgetting previously learned actions. This role is ideal for a researcher with a strong background in video understanding, continual and transfer learning. The intern will work on real-world challenges involving long-horizon human activity videos, and contribute to high-impact publications and patents.
San Jose, CA

 

Key Responsibilities

 
  • Conduct cutting-edge research in action segmentation, and continual learning for procedural video understanding.
  • Design and implement novel algorithms for recognizing and updating action classifiers incrementally as new tasks/classes are introduced with limited supervision.
  • Perform literature review, formulate hypotheses, run experiments, and analyze results.
  • Lead or contribute to research paper writing, including potential submission to top-tier computer vision or machine learning conferences (e.g., CVPR, ICCV, NeurIPS, ECCV).
  • Write well-structured, efficient code using deep learning frameworks such as PyTorch.   

 

Minimum Qualifications

 
  • Currently enrolled in a PhD program in Computer Vision, Machine Learning, Artificial Intelligence, or a closely related field.
  • Publication record in top-tier conferences (e.g., CVPR, ICCV, ECCV, WACV, NeurIPS, ICLR).
  • Prior experience with continual/incremental learning or transfer learning.
  • Prior experience with video encoders.
  • Excellent programming skills,  ability to write reproducible research code, and proficiency in deep learning frameworks, especially PyTorch.
  • Strong written and verbal communication skills.
  • Ability to independently drive research, from ideation to experimentation and publication.

 

Bonus Qualifications

  • Implementation-level experience with generative models (e.g., VAE, GANs, diffusion models).
  • Experience working with long-form procedural videos or temporal segmentation tasks.

 

Years of Work Experience Required  0
Desired Start Date 1/12/2026
Internship Duration 3 Months
Position Keywords Continual learning, video action segmentation, human action understanding

Alternate Way to Apply

Send an e-mail to careers@honda-ri.com with the following:
- Subject line including the job number(s) you are applying for 
- Recent CV 
- A cover letter highlighting relevant background (Optional)

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