[robotics-worldwide] [jobs] Honda Research Institute (Silicon Valley) - Summer internships in Robotics, Motion Planning, Computer Vision, Machine Learning, and more

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[robotics-worldwide] [jobs] Honda Research Institute (Silicon Valley) - Summer internships in Robotics, Motion Planning, Computer Vision, Machine Learning, and more

Behzad Dariush
Honda Research Institute (Silicon Valley) is offering multiple research
internship positions 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.  There are multiple opening in the following
topics.

-        Machine Learning on Time Series Data (Video/Car Sensor Signals)
(Job Number: P17INT-01)
-        Computer Vision based Driving Scene Classification and Event
Detection (Job Number: P17INT-02)
-        Machine Learning / Computer Vision for 3D Scene
Understanding/Reconstruction (Job Number: P17INT-03)
-        Motion Planning / Decision Making (Job Number: P17INT-04)
-        Robotics Manipulation and Navigation (Job Number: P17INT-05)
-        Simulation based Human Factors Study (Job Number: P17INT-06)

More detailed information can be found on our website:
https://urldefense.proofpoint.com/v2/url?u=http-3A__usa.honda-2Dri.com_&d=DwIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=9cbTbNUbE491hPS0efQqOhQr4PJ92k8x0q2Vbnv9NEE&s=Xcdqt2KCanS6EiOWYxE2yxo7Rx3DzPZXIB4Zi2ZDEHA&e=

Also, please see our website for full-time positions.

How to Apply: Please send an e-mail to [hidden email] with the
following:
- Subject line including the job number(s) you are applying for.
- Recent CV
Candidates must have the legal right to work in the U.S.A.

___________________________________________________________________________________
Machine Learning on Time Series Data (Video/Car Sensor Signals) (Job
Number: P17INT-01)
The title includes multiple positions which focus on developing and
evaluating novel machine learning frameworks using on-road driving data
collected from our highly advanced test-vehicles. The candidate is expected
to work on one of the following topics:
- Infer salient objects/regions of the driving video that should attract
driver’s visual attention.
- Model driver situational awareness from scene saliency and driver gaze
behavior.
- Supervised/unsupervised learning of driving behaviors.
- Supervised/unsupervised detection of anomalies.
Qualifications:
- Ph.D. /M.S. candidate in computer science, electrical engineering, or
related field.
- Research experience in computer vision, machine learning and video
analytics.
- Strong background in temporal and multimodal data (e.g. video + time
series) processing.
- 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 is a plus
____________________________________________________________________________
Computer Vision based Driving Scene Classification and Event Detection
(Job Number: P17INT-02)
This title includes multiple positions which offer the opportunity to
conduct innovative research in computer vision, machine learning and data
analysis. The candidate is expected to work on one of the following topics:
- Automatic classification of various driving conditions and scenarios
including place, weather, and traffic condition.
- Detection of driving scene events from video, including ego-centric
events and events associated with other traffic participant behaviors.
Qualifications:
- Ph.D. or M.S. 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 Robot Operating System (ROS).
- Experience in open-source Deep Learning frameworks such as TensorFlow or
Caffe.
- 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-03)
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.
- Multi Lidar based localization.
Qualifications:
- Ph.D. or M.S. 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.
___________________________________________________________________________________
Motion Planning / Decision Making (Job Number: P17INT-04)
This title includes multiple positions which focus developing algorithms to
advance research in motion planning and decision making. The candidate is
expected to work on one of the following topics:
- Develop RL algorithms to address tactical lane changing scenarios.
- Develop RL and IRL algorithms to address merging scenarios.
- Long-term motion prediction using probabilistic or learning-based methods.
- Develop temporal game theoretic models related to autonomous driving for
interactive decision making.
- Identifying outliers when observing traffic vehicles.
Qualifications:
- Ph.D. or highly qualified M.S. students in computer science, electrical
engineering, or related field.
- Excellent programming skills in Python and C++.
- Research expertise in machine learning related techniques, such as RL,
IRL, SVM, CNN, RNN.
- Solid understanding of probabilistic methods, such as Kalman filters,
Particle filters, HMM, DBN, SLDS.
Preferred Qualifications:
- Experience in Robot Operating System (ROS).
- Experience in open-source Deep Learning frameworks such as TensorFlow or
Caffe.
___________________________________________________________________________________
Robotics Manipulation and Navigation (Job Number: P17INT-05)
This title includes multiple positions which focus on formulating and
developing algorithms, and running experiments to advance research in
robotics manipulation and navigation. The candidate is expected to work on
one of the following topics:
- Robotics manipulation using mobile robot platform in the area of
deformable object manipulation.
- Robotics manipulation using manipulator with tactile sensors in the area
of tactile manipulation using machine learning.
- Robotics navigation using mobile robot platform that require close
coordination between navigation planning and stability control.
- Robotics navigation in the area of real-time planning and decision making
using mobile robot platform that navigates through a crowd of pedestrians.
Qualifications:
- Ph.D. or highly qualified M.S. 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 Robot Operating System (ROS).
___________________________________________________________________________________
Simulation based Human Factors Study (Job Number: P17INT-06)
This position offers the opportunity to design and conduct human-factors
study to prototype in-car HMIs on our experimental simulator setups.
Responsibilities:
- Design and conduct the human-factors study to evaluate our prototype HMIs.
- Data analysis to compare subjects’ driving behavior and perception of
each HMI.
Qualification:
- Ph.D. in human factor engineering, or related field.
- Research experience in automotive HMI evaluation.
_______________________________________________
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