[robotics-worldwide] [jobs] Internships at Honda Research Institute USA

ACosgun at hra.com ACosgun at hra.com
Tue Oct 4 12:47:56 PDT 2016

Honda Research Institute USA (HRI-US) is at the cutting edge of Honda's 
research and development activities. HRI-US internship program is designed 
to give students hands-on experience in developing new research ideas. 
Each intern is expected to work closely with HRI-US scientists and 
engineers to generate research prototypes. Interns will have the 
opportunity to publish scientific publications in academic conferences and 
journals. The time frame for these positions may be adjusted to 
accommodate the intern's academic schedule. HRI-US pays competitive 
salaries to interns and provides for a comfortable and exciting research 
environment. Applicants are expected to be pursuing a PhD degree in the 
related areas.  Qualified MS students are also encouraged to apply.

Location: Mountain View, CA
Start Date: January 2017 (flexible)
Duration: 12 weeks minimum

We are looking for experienced and highly motivated students with good 
publication records and excellent analytical and programming skills to 
join our team for Winter 2017!

Behavior Planning for Autonomous Driving (Job Number: P15INT-04)

This position focuses on intelligent decision making for targeted 
autonomous driving applications, using motion planning and machine 
learning techniques. The candidate's responsibilities include: designing 
novel algorithms that make intelligent decisions and learn from previous 
experiences, data processing from several sensors, software development in 
simulation, and time permitting, implementation on the vehicle and 
evaluation the real-time performance of the developed technologies.

·       Research expertise in Motion Planning, Optimization, Machine 
·       Hands-on experience with robots or autonomous vehicles, and Robot 
Operating System (ROS)
·       Excellent programming skills in C++ and/or Python

Visual SLAM (Job Number: P15INT-05)

This position focuses on robot localization, mapping, and SLAM using 
cameras and other sensors like GPS, IMU, and LiDAR. The candidate's 
responsibilities include: designing novel algorithms that enable robust 
visual localization under challenging situations (e.g. varying lighting 
conditions), data processing from camera, LiDAR and other sensors, 
development of the software, and time permitting, implementation on the 
vehicle and evaluation the real-time performance of the developed 

·       Strong knowledge in Computer Vision and Machine Learning
·       Experience in Visual SLAM or Deep Learning is a strong plus
·       Excellent programming skills in C++ and python/MATLAB under Linux

Accelerated Deep Learning Frameworks (Job Number: P15INT-06)

Recent research on deep convolutional neural networks (DCNNs) has focused 
primarily on improving accuracy. However, the state-of-the-art CNN 
networks require tremendous training effort and are too slow for real-time 
computing systems. The goal of this project is to build an efficient deep 
learning pipeline from training to inference for object detection and 
semantic segmentation. The main responsibilities of the candidates 
include: 1) the research and development of new DCNN architectures for 
real-time systems 2) the investigation and implementation of techniques to 
parallelize and accelerate the underlying computation.

·       Research experience in object detection and semantic segmentation
·       Solid understanding of neural networks and the underlying math
·       Hands-on experience in designing deep convolutional neural 
networks using Caffe or similar libraries (Torch, Tensorflow and Theano)
·       Strong background in CUDA and parallel computing. Good 
understanding of GPU architecture is a plus
·       Excellent programming skills in C++ and/or Python

Benchmark SLAM Dataset (Job Number:  P15INT-07)

This project focuses on the problem of creating a comprehensive benchmark 
and evaluation metrics in support of scientific evaluation and objective 
comparison of SLAM, and localization approaches for automated driving and 
robotics applications. The dataset will include recordings on new, 
challenging, and real-world scenarios using synchronized data streams from 
an array of sensors that includes: cameras, LiDAR, GPS, and IMU. It is our 
intention to make this dataset available to the scientific community to 
push the state-of-the-art forward.

·       Experience with visual SLAM, LiDAR SLAM, and multi-sensor fusion 
and calibration. 
·       Familiarity with Robot Operating System (ROS) and Point Clout 
Library (PCL).
·       Excellent programming skills in C++ and/or Python.

How to Apply 
Please send an e-mail to interns at honda-ri.com with the following:
·       Subject line including the job number you are applying for
·       Recent CV
·       A cover letter indicating your desired internship period and 
briefly explaining how you fit to the position

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