Add on 11 April 2019
At Open Robotics, we work with industry, academia, and government to create and support open software and hardware for use in robotics, from research and education to product development. We develop and maintain the core of the ROS and Gazebo. Powered by the support of a global community, these tools are relied upon by hundreds of thousands of users and developers working with every type of robot imaginable. The unifying theme of our team and our work is openness. We use and we build open systems, and we foster an open source community that is at the heart of our projects. We are seeking motivated, friendly, collaborative individuals with an interest in robotics. Direct experience with robotics is a plus, but not a requirement. All positions are preferred to be full-time and on site at one of our offices (Mountain View, California or Singapore). However, we are open to the possibility of part time and offsite opportunities. Our current openings (https://urldefense.proofpoint.com/v2/url?u=https-3A__www.openrobotics.org_careers-23BambooHR&d=DwIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=wlYki35iw-oPDEGH9zOl882MGjaT1E5Oac_OI5k6aXU&s=Vs1bWAuNjZn7RG-wasjwwMX4a49O78dC3uaqT3UUBhw&e=) include: * Open Source Evangelist * Technical Project Manager * Technical Writer * Software Engineer: Robotics (California and Singapore) * Software Engineer: Web : (California and Singapore) We're also looking for excellent interns (though we're already full for summer 2019 in California): https://urldefense.proofpoint.com/v2/url?u=https-3A__www.openrobotics.org_interns&d=DwIBaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=wlYki35iw-oPDEGH9zOl882MGjaT1E5Oac_OI5k6aXU&s=fN3njzb2KzZ-XTgjIPzoONXHlgxh7BvA9SgztyZxZ2o&e=.
Add on 11 April 2019
MERL is looking for a highly motivated intern to work on developing algorithms for robot learning using learning from demonstration, imitation learning and/or deep reinforcement learning. Successful candidate will collaborate with MERL researchers to design, analyze, and implement new algorithms, conduct experiments, and prepare results for publication. The candidate should have a strong background in (deep) reinforcement learning, Imitation Learning (or Learning from Demonstrations, LfD), machine learning and robotics. Prior experience of working with robotic systems is required. The candidate should be comfortable implementing the developed algorithms in Python and should have prior experience working with ROS. Prior exposure to deep learning and hands-on experience with packages such as Pytorch and/or Tensorflow is expected. The candidate is expected to be a PhD student in Computer Science, Electrical Engineering, Operations Research, Statistics, Applied Mathematics, or a related field, with relevant publication record. Expected duration of the internship is at least 3 months. The position is expected to be available starting late August or early September. Interested candidates are encouraged to apply with their recent CV with list of related publications and links to GitHub repositories (if any). If interested, please apply using the following link <https://urldefense.proofpoint.com/v2/url?u=http-3A__www.merl.com_internship_openings.php-3Ftags-3Djha&d=DwIFAw&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=CO15iBNeO0rsX7OtSuVyqwz5jrzEKmxPFvFoIE-xyvI&s=Zoq-FU1Gcsy66Rxd4P01nW8LSs0p3-G3CTe6b3OkMxk&e=>https://urldefense.proofpoint.com/v2/url?u=http-3A__www.merl.com_internship_openings.php-3Ftags-3Djha&d=DwIFAw&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=CO15iBNeO0rsX7OtSuVyqwz5jrzEKmxPFvFoIE-xyvI&s=Zoq-FU1Gcsy66Rxd4P01nW8LSs0p3-G3CTe6b3OkMxk&e= To know more about MERL, please visit www.merl.com<https://urldefense.proofpoint.com/v2/url?u=http-3A__www.merl.com&d=DwIFAw&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=CO15iBNeO0rsX7OtSuVyqwz5jrzEKmxPFvFoIE-xyvI&s=PE1I1NIww0XBtD6uON2ZGsqdknkmlnFNaHy7MtoLtN0&e=> If you have questions, please contact me at devesh.jha at merl.com
Add on 11 March, 2019
InnoCoRe (Innovation and collaborative Research) team is a multidisciplinary team of “Comfort and Driving Assistance” (CDA) Business Group. The team’s objective is to explore the fields of autonomous driving, connected car and user interaction for new technologies and new use cases. Our work helps defining Valeo’s roadmaps (5-10 years), providing R&D teams with innovative projects to pursue Engineers, UX designers and project managers located in France, Germany and California team-up around a common mission to design and experiment new concepts and services to create added value for existing Valeo technologies. Their collaboration with Valeo’s academic network and start-ups ecosystem is key for leveraging scientific expertise and agility within projects. Project: Driving Situation A driving situation corresponds to a representation of the world collected and/or perceived around a main vehicle in a given instantaneous moment. This representation is composed of (a) the information that can be collected in a moment by sensors (Cameras, Lidar, GPS) and (b) information coming from other services, e.g. related to the road and the weather. A Situation can be useful to understand the own vehicle status, understand the status of the surrounding environment and understand the state of the perceived objects. These key elements defines the “driving situation” that the driver is currently facing. Hence, the analysis of a sequence of these instants can lead to a near future decisions. The missions You’ll work within the project driving situations in the following topics. State of the art: Study and implementation of methodologies such as Markov Chain and Markov Decision Processes (MDP) for multi dimensional state spaces. Feature extraction and Algorithm development: Extract relevant information given a set of data either with feature engineering or machine learning techniques, e.g. SVM, PCA, CNN, LSTM, and Auto-encoders. Metric Analysis: Compare performance of the developed algorithms based on either state of the art scoring systems or ad-hoc systems. Technical Tools We are searching for highly motivated, curious and independent students with the following knowledge: - General purpose programming language (Python, C++) - First hands-on experience with a Machine Learning/Deep Learning framework (i.e. Scikit-learn, Tensorflow, PyTorch) - Full proficiency in English (speaking, writing) - 2nd year of Master’s Degree in Robotics, Computer Science, Applied Mathematics or Similar. Good to have: - Familiarity in using a multisensor middleware (i.e. ROS, RTMaps) - Familiarity with simulators (Gazebo, ODE, Carla) - Experience in coding with OpenCV - Knowledge about publisher / subscriber systems (i.e. ZeroMQ, MQTT, RabbitMQ) - Containerization (Docker) and orchestration (swarm, kubernetes) - Driving License Contact Please send your applications to omar.islas at valeo.com and add julien.moizard at valeo.com and kevin.nguyen at valeo.com to copy. -- *This e-mail message is intended for the internal use of the intended recipient(s) only. The information contained herein is confidential/privileged. Its disclosure or reproduction is strictly prohibited. If you are not the intended recipient, please inform the sender immediately, do not disclose it internally or to third parties and destroy it. In the course of our business relationship and for business purposes only, Valeo may need to process some of your personal data. For more information, please refer to the Valeo Data Protection Statement and Privacy notice available on Valeo.com
Add on 14 March, 2019
We are seeking to fill a funded Ph.D. opening in the area of optical and acoustic seafloor mapping. Possible topics include terrain reconstructions, real-time adaptive path planning, habitat classification, and SLAM. The student will participate in field work and develop a thesis that mixes oceanographic science and marine robotics using a number of existing vehicles and sensor systems. The student could enroll in the URI Ocean Engineering Department or the Graduate School of Oceanography depending on their prior education and desired degree. - Desired skill set Background in computer science and/or engineering Programming experience in Python, C++ or MATLAB Familiarity with ROS and/or LCM, or mobile robots in general - Contact Please contact Dr. Chris Roman, croman2 at uri.edu ====================================== Chris Roman, Ph.D. Professor of Oceanography University of Rhode Island Graduate School of Oceanography 215 South Ferry Road Narragansett RI 02882 *croman2 at uri.edu <croman2 at uri.edu>* Phone 401-874-6115 Fax 401-874-6811
Add on 4 September, 2018
We are always looking for interns that help us maintain and enhance our ROS packages.
Your internship starts with getting to know our robots and current ROS packages in detail.
Run our robots in Gazebo simulations.
Evaluate new packages (localization, navigation, simulation, …) through practical tests on our demo units and help us decide which modules to replace or update.
Add new features to Neobotix ROS packages.
Develop new packages for our mobile robots.
You are studying computer science, mechatronics, robotics or a similar course.
Previous experience with ROS is obviously a huge plus.
You have programming knowledge in C++ and Python.
You want to actively engage in the ROS community and in taking ROS forward.
You have sufficient English language skills to document and discuss your work results.
You are able to work in Heilbronn, Germany.
What we offer:
A chance to get your hands on actual autonomous mobile robots.
A multitude of interesting tasks.
A comfortable working-climate and a flexible work schedule.
The chance to develop innovative robot systems and see them come to live.
We are looking forward to your application (reference ID ROS ) via e-mail to firstname.lastname@example.org
Add on 21 August, 2018
WHAT WE HAVE TO OFFER