A few available positions are listed below. However, this list is not always up-to-date. So, if you are interested in our group’s work and satisfy above requirements, send an email to learn more about potential positions.
Multiple post-doc positions for the DARPA SubTerranean Challenge project (available immediately)
Post-doc in integrated mission and motion planning: for prototype Mars copter and rover (available immediately)
NASA-JPL/Caltech in Pasadena, California has a couple of openings for post-doc. The main topic is “integrated mission and motion planning: for prototype Mars copter and rover”. This is a joint project between JPL and Caltech with PIs from JPL’s robotics and GNC sections and Caltech’s Control and Dynamical Systems and Mechanical Department. Positions are available immediately.
The job function includes active participation and contribution to JPL's activities related to robotic autonomy, controls, and computer vision. Activities include: theoretical analysis, software development in C++/ROS/Linux, participating in proposal development, and submission of technical papers to journals/conferences.
Strong background in at least 3 of the following areas is required:
- Formal methods (such as LTL)
- Integrated task and motion planning
- Motion planning under uncertainty and belief space planning
- MDPs and POMDPs
- Semantic mapping and scene understanding
- Localization and 3D geometric mapping
- Collision avoidance algorithms
- Flying vehicles (control, estimation, landing, …)
Required Skills (varies for different project):
- Coding skills in C++/Python
- Experience with Robot Operating System (ROS)
- Strong written and verbal communications skills
Apply
Interested candidates should send their resume and the earliest date of availability to the recruiting team at mobility.applicant@jpl.nasa.gov,
with email subject [postdoc 2017 Copter-Rover].
About JPL
The Jet Propulsion Laboratory (JPL) is NASA’s lead center for robotic exploration of the Solar System. JPL’s core competency is the end-to-end implementation of robotic space missions to study Earth, the Solar System, and the Universe. JPL is part of NASA and California Institute of Technology (Caltech).
For more information on JPL Robotics, please visit: http://www-robotics.jpl.nasa.gov
For more information on JPL postdoctoral programs, please visit: Postdocs.jpl.nasa.gov
Post-doc in motion planning under uncertainty
The Jet Propulsion Laboratory (JPL) in Pasadena, California has an opening for a post-doc in the area of integrated motion planning under uncertainty and belief space planning, with applications to autonomous navigation of prototype rovers and rotorcrafts on Mars.
The job function includes active participation and contribution to JPL's activities related to robotic autonomy, controls, and computer vision. Activities include: theoretical analysis, software development in C++/ROS/Linux, participation in grant proposal development, and submission of technical papers to conferences/journals.
Background
- Motion Planning Under Uncertainty and Belief Space Planning
- Optimization and Real-time Trajectory Generation
- Robot Localization and Mapping
- Sampling-based Robot Motion Planning Methods
- Collision Avoidance Algorithms
- Control Theory
- Stochastic Differential Equations
Software Skills
- Demonstrated programming skills in C++/Python
- Experience with Robot Operating System (ROS)
- Strong written and verbal communications skills
Apply
Interested candidates should send their resume and date of availability to mobility.applicant@jpl.nasa.gov, with email subject [Post-Doc 2017 Autonomy].
About JPL
The Jet Propulsion Laboratory (JPL) is NASA’s lead center for robotic exploration of the Solar System. JPL’s core competency is the end-to-end implementation of robotic space missions to study Earth, the Solar System, and the Universe. JPL is part of NASA and California Institute of Technology (Caltech). Find more information on JPL Robotics at http://www-robotics.jpl.nasa.gov.
Summer 2017 Internship
Planning under motion and sensing uncertainty is one of the fundamental problems in robotics. Belief space planning and POMDPs (Partially Observable Markov Decision Processes) are principled frameworks to describe this problem. However, the solution to POMDP in realistic setting with continuous state/action/observation spaces is computationally intractable. Finding approximate solutions to this problem with plausible features is an ongoing research in robotics community.
Project description
This project is concerned with the problem of planning under motion and sensing uncertainty for robotic applications. In particular, we rely on sampling-based techniques in motion planning to create an anytime solution for this problem. We start with a coarse solution and enhance it over time by further sampling the belief space, and updating the resulting motion plan.
There are multiple positions with focus on theory or implementation. Please mention in the email your preference (theory or implementation). If you are comfortable with both, you are strongly encouraged to apply.
The theoretical work in this project will be partially related to the paper on FIRM. The implementation work in this project will be related to OMPL .
Background
- Motion Planning Under Uncertainty and Belief Space Planning
- Optimization and Real-time Trajectory Generation
- Robot Localization and Mapping
- Sampling-based Robot Motion Planning Methods
- Collision Avoidance Algorithms
- Estimation and Control Theory
- Stochastic Differential Equations
Familarity with at least half of the above areas is required.
Skills
- Solid fundamentals in linear algebra, probability theory, and statistics
- Demonstrated programming skills in C++/Python
- Experience with Robot Operating System (ROS)
- Strong written and verbal communications skills
- Comfortable with development in Linux
Apply
Interested candidates should send their resume and date of availability to to mobility.applicant@jpl.nasa.gov with the following email address:
- For US citizens and permanent residents use [intern-US 2017 Autonomy] as the email subject.
- Otherwise, use [intern 2017 Autonomy] as the email subject.
Some of the positions are limited to US citizens and permanent residents.
About JPL
The Jet Propulsion Laboratory (JPL) is NASA’s lead center for robotic exploration of the Solar System. JPL’s core competency is the end-to-end implementation of robotic space missions to study Earth, the Solar System, and the Universe. JPL is part of NASA and California Institute of Technology (Caltech). Find more information on JPL Robotics at http://www-robotics.jpl.nasa.gov.
Summer 2017 Internship
Planning under motion and sensing uncertainty is one of the fundamental problems in robotics. Belief space planning and POMDPs (Partially Observable Markov Decision Processes) are principled frameworks to describe this problem. However, the solution to POMDP in realistic setting with continuous state/action/observation spaces is computationally intractable. Finding approximate solutions to this problem with plausible features is an ongoing research in robotics community.
Project description
This project is concerned with the problem of planning under motion and sensing uncertainty for robotic applications. In particular, we rely on sampling-based techniques in motion planning to create an anytime solution for this problem. We start with a coarse solution and enhance it over time by further sampling the belief space, and updating the resulting motion plan.
There are multiple positions with focus on theory or implementation. Please mention in the email your preference (theory or implementation). If you are comfortable with both, you are strongly encouraged to apply.
The theoretical work in this project will be partially related to the paper on FIRM. The implementation work in this project will be related to OMPL .
Background
- Motion Planning Under Uncertainty and Belief Space Planning
- Optimization and Real-time Trajectory Generation
- Robot Localization and Mapping
- Sampling-based Robot Motion Planning Methods
- Collision Avoidance Algorithms
- Estimation and Control Theory
- Stochastic Differential Equations
Familarity with at least half of the above areas is required.
Skills
- Solid fundamentals in linear algebra, probability theory, and statistics
- Demonstrated programming skills in C++/Python
- Experience with Robot Operating System (ROS)
- Strong written and verbal communications skills
- Comfortable with development in Linux
Apply
Interested candidates should send their resume and date of availability to to mobility.applicant@jpl.nasa.gov with the following email address:
- For US citizens and permanent residents use [intern-US 2017 Autonomy] as the email subject.
- Otherwise, use [intern 2017 Autonomy] as the email subject.
Some of the positions are limited to US citizens and permanent residents.
About JPL
The Jet Propulsion Laboratory (JPL) is NASA’s lead center for robotic exploration of the Solar System. JPL’s core competency is the end-to-end implementation of robotic space missions to study Earth, the Solar System, and the Universe. JPL is part of NASA and California Institute of Technology (Caltech). Find more information on JPL Robotics at http://www-robotics.jpl.nasa.gov.