Currently, HRI-US (Silicon Valley) is offering research internships to highly motivated PhD (and qualified MS) students.  Interns will work closely with HRI researchers, and publishing results in academic forums is highly encouraged.  We are looking for candidates with good publication track records and excellent programming skills to join our team!

3D Computer Vision in Dynamic Traffic Scenes (Job Number: P17INT-08 )
Mountain View, CA

This project focuses on development of computer vision and machine learning algorithms related to processing and fusion of 2D video and 3D point cloud data, including segmentation, recognition, registration, and tracking.    The project scope includes analysis, reconstruction, and interpretation of 3D dynamic scenes through fusion of video and LiDAR point cloud data.

 

Qualifications:

  • MS or PhD candidate in computer science, electrical engineering, or related field
  • Strong familiarity and research experience in 3D computer vision and machine learning
  • Hands-on experience in one or more of the following: LIDAR data processing, simultaneous localization and mapping (SLAM), perception, sensor fusion
  • Highly proficient in software engineering using C++ and Python
  • Experience with Point Cloud Library (PCL), Robot Operating System (ROS), and GPU programming preferred
  • Experience in open-source Deep Learning frameworks such as TensorFlow or Caffe preferred
Traffic Scene Classification from Video (Job Number: P17INT-09 )

This project focuses on research and development of computer vision and machine learning algorithms for video based classification/recognition of road scenes, including places, road surface and weather conditions, and spatial relationships.  This core technology is to be used for higher level understanding of traffic scenes, including temporal event detection, action recognition, video captioning, and localization.

 

Qualifications:

  • MS or PhD candidate in computer science, electrical engineering, or related field
  • Strong familiarity with machine learning techniques pertaining to visual recognition, place recognition, and/or video classification
  • Highly proficient in software engineering using C++ and Python
  • Experience in TensorFlow (or Caffe) and CAD rendering tools preferred
Machine Learning (Job Number: P17INT-11 )
Mountain View, CA

This position focuses on developing learning framework for video saliency in driving scene utilizing a unique on-road driving data that includes scene videos, vehicle states as well as expert drivers' gaze information.

 

Key Responsibilities:

  • Develop novel machine learning algorithm and evaluate the performance on video saliency estimation
  • Develop meaningful metrics to evaluate the proposed approach

 

Qualifications:

  • PhD candidate in computer science, electrical engineering, or related field
  • Strong familiarity and research experience in computer vision, machine learning, including sequential modeling, multimodal signal fusion, and deep learning
  • Excellent programming skills in Python and C++
  • Experience in TensorFlow (or Cafee) preferred
Human-Based Computation and Crowdsourcing (Job Number: P17INT-13 )
Mountain View, CA

This position offers the opportunity to study human-computing for crowdsourcing based methods to accelerate data acquisition and quality control for machine learning applied to computer vision-based systems.

 

Responsibilities:

  • Study and design crowdsourcing interfaces and analyze collected data
  • Apply machine learning-based data cleaning/selection algorithm to the collected data
  • Train machine-learning algorithm using the collected data and compare performances

 

Qualification:

  • PhD candidate in computer science, electrical engineering, or related field
  • Research experience in computer vision, machine learning, human machine interaction
  • Experience designing deep neural networks using TensorFlow, Keras or similar tools
  • Excellent programming skills in Python (C++)
  • Strong publication record in top tier conference/journal in computer vision and machine learning areas preferred
Robotic Manipulation of Deformable Objects (Job Number: P17INT-16 )
Mountain View, CA

Key responsibilities:

Formulate and develop algorithms into codes, and run experiments using mobile robot platform in the area of deformable object manipulation deep reinforcement learning

 

Qualifications:

  • PhD or highly qualified MS candidate in computer science, electrical engineering, or related field
  • Experience in motion planning, manipulation/grasping, and machine learning
  • Experience in setting up simulation environment and executing real robot experiments
  • Good programming skills in either C++ or Python
  • Experience with ROS, and deep RL preferred
Robotic Cooperative Manipulation (Job Number: P17INT-17 )
Mountain View, CA

Key responsibilities:
Formulate and develop algorithms into code, and run experiments using mobile robot platform in the
area of sequence generation for object manipulation


Qualifications:

  • PhD or highly qualified MS candidate in computer science, electrical engineering, or related field
  • Experience in motion planning, manipulation/grasping, and machine learning
  • Experience in setting up simulation environment and executing real robot experiments.
  • Good programming skills in either C++ or Python
  • Experience in using ROS and deep learning preferred
Robotics Tactile Manipulation (Job Number: P17INT-18 )
Mountain View, CA

Key responsibilities:

Formulate and develop algorithms into codes, and run experiments using manipulator with tactile sensors in the area of tactile manipulation and machine learning

 

Qualifications:

  • PhD or highly qualified MS candidate in computer science, electrical engineering, or related field
  • Experience in tactile sensing, manipulation/grasping, and machine learning and deep reinforcement learning
  • Experience in setting up simulation environment and executing real robot experiments
  • Good programming skills in either C++ or Python
  • Experience with ROS and hierarchical learning preferred
Motion Planning/Decision Making (Job Number: P17INT-19 )
Mountain View, CA

Key responsibilities:

  • Develop RL algorithms to develop decision making and motion planning algorithms
  • Develop IRL/LfD/Behavior Cloning algorithms to address driving scenarios

 

Qualifications:

  • Excellent programming skills in Python and C++
  • Research expertise in Machine Learning related techniques including RL and IRL/LfD/Behavior Cloning
  • Experience in TensorFlow or PyTorch preferred
Vehicle Motion Prediction (Job Number: P17INT-20 )
Mountain View, CA

This position will focus on long-term vehicle motion prediction using probabilistic or learning-based methods. We will use both simulated data as well real data gather from on-board sensors to predict the intention and future trajectory of surrounding vehicles. Key responsibilities include: (1) literature survey (2) problem formulation and modeling (3) performing proof-of-concept using simulation, and (4) code development and validation using real sensor data.

 

Qualifications:

  • Good programming skills in either C++ or Python
  • Solid understanding of probabilistic methods such as Kalman filters, Particle filters, HMM, DBN, SLDS
  • Working knowledge of machine learning techniques such as SVM, CNN, RNN
Computer Vision: Traffic Scene Understanding (Job Number: P17INT-21 )
Mountain View, CA

This title includes multiple positions which offer the opportunity to conduct innovative research in computer vision, machine learning, and video analytics.  The candidate is expected to work on one of the following topics:

  • Human behavior understanding, including human pose estimation, action detection, intention prediction, and trajectory forecasting
  • Captioning and retrieval of traffic scene events from video
  • Automatic classification of various driving conditions and scenarios including place, weather, and traffic condition
  • Detection and prediction of traffic participant actions from video

 

Qualifications:

  • PhD or highly qualified MS candidate in computer science, electrical engineering, or related field
  • Research experience in machine learning, computer vision and/or driver behavior data analytics
  • Highly proficient in software engineering using C++ and Python

 

Preferred Qualifications:

  • Experience in open-source Deep Learning frameworks such as TensorFlow or Caffe
  • Familiarity with graphical models (e.g. probabilistic graphical models, scene graphs)
  • Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents​​​​​
Machine Learning/Computer Vision for 3D Scene Understanding/Reconstruction (Job Number: P17INT-22 )

This title includes multiple positions which focus on research and development of computer vision, machine learning and optimization algorithms.  The candidate is expected to work on one of the following topics:

  • 3D traffic scene reconstruction from video
  • Joint 2D/3D Data Fusion for Dynamic Traffic Scene Analysis

 

Qualifications:

  • PhD or MS in computer science, electrical engineering, or related field
  • Strong familiarity with computer vision and machine learning techniques pertaining to 3D reconstruction, SLAM, visual recognition, and deep learning
  • Highly proficient in software engineering using C++ and Python

 

Preferred Qualifications:

  • Experience in open-source Deep Learning frameworks such as TensorFlow or Caffe
  • Hands-on experience in developing algorithms for 3D reconstruction, SLAM, and visual recognition
  • Experience in Robot Operating System (ROS)
  • Strong written and oral communication skills including development and delivery of presentations, proposals, and technical documents
  • Strong publication record in one or more of the following areas: computer vision, machine learning
How to apply

​Please send an email to careers@honda-ri.com with the following:

  • ​​Subject line including the ​job number you are applying for
  • Recent CV
  • A cover letter explaining how your background matches the qualifications
Candidates must have the legal right to work in the U.S.A.​