Currently, HRI-US (Silicon Valley) is offering research internships to highly motivated Ph.D. (and qualified M.S.) 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!

Human Behavior Understanding and Prediction (Job Number: P18INT-09 )
San Jose, CA

The title includes multiple positions which focus on developing computer vision and machine learning algorithms for analysis, prediction, and understanding of human behavior in various domains to support on-going research on next generation intelligent mobility systems. The candidate is expected to work on one of the following topics:

  • Future trajectory forecast and human intention prediction in a public environment
  • Driver state / activity understanding for in-cabin monitoring
  • Human pose estimation / tracking in indoor and outdoor environments
  • Creation of a benchmark human activity dataset

Qualifications:

  • Ph.D. /M.S. candidate in computer science, electrical engineering, or related field
  • Strong research experience in computer vision and machine learning
  • Hands-on experience in one or more of the following: trajectory forecast, future prediction, activity recognition, hand pose estimation, human pose estimation, pose tracking
  • Experience in open-source deep learning frameworks such as TensorFlow or PyTorch preferred
  • Excellent programming skills in Python or C++
Computer Vision and Machine Learning in Traffic Scenes (Job Number: P18INT-10 )
San Jose, CA

The title includes multiple positions which focus on developing computer vision and machine learning algorithms to capture the detailed semantics of 2D and/or 3D traffic scenes. The candidate is expected to work on one of the following topics:

  • Capturing the semantics of visual scenes by explicit modeling objects, their attributes, and relationships to other objects and the environment
  • Segmentation, recognition, registration, and tracking through fusion of 2D video and 3D LiDAR point cloud data
  • Analysis, reconstruction, and interpretation of 3D dynamic scenes
  • Higher level classification/recognition of dynamic traffic scenes including place, conditions, and spatial relationships using temporal event detection, action recognition, and localization
  • Multi-modal sensor fusion (cameras, LiDARs, and radars) for detection / classification with uncertainty

Qualifications:

  • Ph.D. /M.S. candidate in computer science, electrical engineering, or related field
  • Strong familiarity with computer vision and machine learning techniques pertaining to scene understanding, image classification, and object detection
  • Hands-on experience in one or more of the following: probabilistic graphical models, scene graphs, spatio-temporal graphs, SLAM, sensor fusion, visual recognition, video classification, LiDAR processing
  • Experience in open-source deep learning frameworks such as TensorFlow or PyTorch preferred
  • Excellent programming skills in Python or C++
  • Experience with Point Cloud Library (PCL), Robot Operating System (ROS), and GPU programming is a plus for some topics
Video-based Captioning and Retrieval in Traffic Scenes (Job Number: P18INT-11 )
San Jose, CA

This internship position focuses on developing computer vision and machine learning algorithms to describe (or caption) more complex events that are important in traffic scene understanding and enable retrieval of these events based on key-words, linguistic description, graphical representation, or video similarity based search methods.

Qualifications:

  • Ph.D. /M.S. candidate in computer science, electrical engineering, or related field
  • Strong familiarity with computer vision and machine learning techniques pertaining to video captioning and retrieval
  • Experience in open-source deep learning frameworks such as TensorFlow or PyTorch preferred
  • Excellent programming skills in Python or C++
Driving Style Characterization (Job Number: P18INT-12 )
San Jose, CA

This project focusses on development of computer vision and machine learning algorithms for characterization of driving styles or behaviors unique to individuals. The project involves supporting the creation of a driving behavior – personality dataset which involves developing perception, cognition, emotion, and social acumen via analyzing data from sensors such as CAN, camera, LiDAR and GPS/IMU.

Qualifications:

  • Ph.D. /M.S. candidate in computer science, electrical engineering, or related field
  • Strong familiarity and experience in machine learning, data analytics and computer vision
  • Highly proficient in C++ and Python
  • Experience with simulation platforms such as CARLA is a plus
  • Experience / interest in on-the-road social psychology is a plus
Explainable AI (Job Number: P18INT-13 )
San Jose, CA

The title includes multiple positions which focus on behavior cloning models using computer vision and machine learning algorithms with emphasis on human-interpretable network. The candidate is expected to work on one of the following topics:

  • Utilizing semantic modeling, reasoning, and inference paradigm to explain model output
  • Exploiting driving domain knowledge based constrains to ensure safety and rule following

Qualifications:

  • Ph.D. /M.S. candidate in computer science, electrical engineering, or related field
  • Strong familiarity with computer vision and machine learning techniques pertaining to XAI
  • Experience in one or more of the following topics: Network attention, graph neural network, knowledge/scene graph preferred
  • Experience in open-source deep learning frameworks such as TensorFlow or PyTorch preferred
  • Excellent programming skills in Python
Motion Planning / Decision Making (Job Number: P18INT-14 )
San Jose, CA

This title includes multiple positions which focus on developing algorithms to advance research in motion planning and decision making. The candidate is expected to work on one of the following topics:

  • Developing control and planning algorithms for following a pedestrian across rugged terrain
  • Intention-aware decision making for steering and speed control to handle merging with one of the following scenarios: dense traffic, slow and continuous traffic flow of cars, different speed limits, etc

Qualifications:

  • Ph.D. /M.S. candidate in computer science, electrical engineering, or related field
  • Strong familiarity and research experience in some or more of the following: path planning, re-planning, anytime planning, SLAM, active learning, reinforcement learning, bandit problems
  • Experience in open-source deep learning frameworks such as TensorFlow or PyTorch preferred
  • Excellent programming skills in Python or C++
Robotics: Manipulation (Job Number: P18INT-15 )
San Jose, CA

This title includes multiple positions which focus on implementing and developing algorithms as well as running experiments to advanced research in robotics manipulation. The candidate is expected to work on one of the following topics:

  • Robotics manipulation of deformable objects such as bed sheets and wire harnesses
  • Developing algorithms that allow robots to manipulate objects cooperatively with humans using learning from demonstration techniques
  • Robotics manipulation using tactile sensors in unstructured environments

Qualifications:

  • Ph.D. or highly qualified M.S. candidate in computer science, electrical engineering, or related field
  • Good programming skills in either C++ or Python
  • Experience in deep learning and other machine learning methods such as reinforcement learning and human-in-the-loop online learning
  • Experience in Robot Operating System (ROS)
  • Experience in the following is a plus for some topics: tactile sensing, manipulation, grasping, real robots, or physics engine such as MuJoCo and Bullet
Robotics: Physical Human-Robot Interaction (Job Number: P18INT-16 )
San Jose, CA

This title includes multiple positions which focus on formulating and developing algorithms as well as running user studies of teleoperated / autonomous physical human-robot interaction (pHRI). The candidate is expected to work on one or more of the following topics:

  • Force and motion control for pHRI
  • Hardware and software integration of the teleoperation system
  • Interaction modeling from human demonstations
  • Human intention recognition for pHRI
  • Planning, preparation and execution of user studies

Qualifications:

  • Ph.D. or highly qualified M.S. candidate in computer science, mechanical engineering, or related field
  • Experience in robot kinematics/dynamics, force control, or human motion analysis
  • Experience in setting up and executing real robot experiments using ROS
  • Experience in setting up and executing user studies involving robot hardware
  • Excellent programming skills in C++ or Python
Robotics: Machine Learning for Navigation (Job Number: P18INT-17 )
San Jose, CA

This internship position focuses on constructing movement algorithms for robots in human populated environments that considers both classical metrics (e.g., safety and efficiency) and social robotics metrics (e.g., human proximity preference, multifaceted human intent, and human flexibility).

Qualifications:

  • Ph.D. or highly qualified M.S. candidate in computer science, electrical engineering, or related field
  • Experience in machine learning (adversarial reinforcement learning/Bayesian neural networks, and stochastic processes such as Dirichlet and Gaussian processes), control theory, and optimization
  • Experience training and testing on existing public datasets, running simulation studies in Gazebo, and running a medium scale (5 people) experiment on a real platform
Robotics: Exploration of Spatial Representations in the Scene (Job Number: P18INT-18 )
San Jose, CA

This title includes multiple positions which focus on exploring object-level state representations to describe the scene. The candidate is expected to work on one or more of the following topics:

  • Develop learnable modes of behavior that bias exploration in autonomous agents
  • Discovering object-level representations of the scene to formulate priors for predictions
  • Designing adaptive spatial representations that better focus explorations in higher dimensions

Qualifications:

  • Ph.D. or highly qualified M.S. candidate in computer science, mechanical engineering, or related field
  • Strong familiarity and research experience in some or all of the following fields: Machine Learning, Reinforcement Learning, knowledge representations, and video prediction
  • Excellent programming skills in C++ or Python
Nanoparticle Synthesis and Characterization (Job Number: P18INT-19 )
San Jose, CA

This position offers the opportunity to work on nanoparticle solution synthesis and characterization. The candidate must possess excellent interpersonal and communication skills, eagerness to learn and grow, and have a flexible approach to solving problems.

Job Responsibilities:

  • Participate in exploring and developing efficient methods for  the solution synthesis and surface modification of inorganic nanomaterials such as metal nanoparticles and their alloys
  • Develop simple methods to improve the dispersion of inorganic nanomaterials
  • Characterize and analyze the nanomaterials through SEM, XRD, Raman, UV-Vis, FT-IR, TGA, and so on
  • Work with supervisor, as needed, in resolving synthetic and characteristic process problems
  • Demonstrate efficient and safe work practices with a high level of diligence
  • Present the results through presentations and scientific publications

Qualifications:

  • ​Ph.D. candidate in Chemistry, Chemical Engineering, Materials Science or related field, with rich experiences in solution synthesis, separation of nanomaterials and characterization
  • Experience with surface science and functionalization, ink formulation processes preferred
  • Strong written and oral communication skills, good team worker

Duration:

  • 4 – 6 months
Highly Sensitive and Selective Gas Sensors (Job Number: P18INT-20 )
San Jose, CA

This position offers the opportunity to develop highly sensitive and selective gas sensors based on nanoparticles and carbon nanotubes. The candidate must possess excellent interpersonal and communication skills, eagerness to learn and grow, and have a flexible approach to solving problems.  


​Job Responsibilities:

  • ​Participate in developing the next generation of gas sensors targeting challenging applications such as environmental gas sensing
  • Establish automated gas sensor measurement and gas flow control through a computer
  • Carry out senor performance studies upon exposure to various gas species
  • Work with supervisor in resolving sensor signal detection and characteristic process problems
  • Present the results through presentations and scientific publications

Qualifications:

  • ​Ph.D. candidate in Electrical Engineering, Materials Science, Physics or related field
  • Hands-on experience in electrical measurements and familiarity to lab tools such as oscilloscope and data logger
  • Experience with analog circuit design, firmware programming, and circuit board design
  • Excellent ability to identify and solve problems
  • Strong written and oral communication skills, good team worker

Duration:

  • 4 – 6 months
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.​