This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requiring that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
Position description
The Automated Vehicle (AV) program at NIST is seeking a candidate to work on a project related to the robustness of AI perception for self-driving cars. NIST is leading a multidisciplinary effort which aims at developing a testbed (physical and simulated) to test on-road driving scenarios when facing perturbations (natural and deliberate/adversarial) on the roadway. The project requires a candidate with multidisciplinary skills that will execute multiple tasks which focus on AI perception and decision-making testing, evaluation, and integration with a physical testbed (physical vehicle). The candidate will follow guidance from the project leaders.
Key responsibilities will include but are not limited to:
- Expand the AI perception (object detection and classification) testing capabilities to assess their robustness and readiness for on-road use by incorporating LIDAR and camera data, including estimation of uncertainties in detection and classification.
- Investigate the impact of uncertainties on other critical systems, such as decision-making and path planning.
- Work on developing a public-facing Web portal to host services that expose advanced AI perception testing capabilities tailored to the needs of the AV community of stakeholders. Coordinate with external stakeholders to ensure smooth technology transfer.
- Write papers to describe current work and submit to journals with a focus on AI perception and decision-making efforts.
- Align AI perception and decision-making work with other NIST AV teams using collaboration and communication.
- Draft test plans for AI team further assisting with designing uncertainty experiments in CARLA and participate in weekly discussions.
- Assist in implementing software packages and prototypes using ROS2 and python to use AI models for perception and decision-making for deploying current AI efforts on the development mule (NIST autonomous vehicle).
Qualifications
- PhD or (BS + 5 years of experience) in the following or related fields (Computer Science, Electrical engineering, Mechanical engineering, Computer engineering, Robotics)
- Experience with programming in Python and C++.
- Experience with PyTorch or TensorFlow for AI model development and testing.
- Experience with AI model development and testing, including uncertainty associated with detection and classification.
- Experience with AI model hosting platforms (e.g., Ultralytics)
- Good knowledge and skills with ROS2 on Linux systems.
- Be able to work on both Linux and Windows
- Experience with version control software and workflow (Git/Github/Gitlab)
Other relevant experience:
- Experience in measurement, testing, and evaluation of software.
- Report writing and making presentations with relevant figures/illustrations/data.
- Strong oral and written communication skills that convey ideas and work in an efficient manner.
- Good documentation of the work that enables reproduction of the tests and results.
Please upload the following (preferably in a single PDF) with your application:
- CV/Resume
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Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor’s degree holders, graduate students, master’s degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.
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