Assistant Research Scientist (PREP0004217) Full-time

Assistant Research Scientist

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.

Research Title: Measurement Science for AI Decision-Making in Automated Driving Systems

The work will entail:

• Building and curating a scenario database for decision-making evaluation
• Developing scenario classification and tagging systems to support systematic evaluation of behavioral competencies
• Implementing tools for scenario selection, parameterization, and configuration for use in simulation-based testing
• Creating methods for generating scenario variants to ensure comprehensive coverage of edge cases and challenging traffic situations
• Designing and implementing a standardized format for representing vehicle state information exchanged between the simulation environment and the automated driving (AD) stack under test
• Defining world state schemas that capture relevant traffic context, road geometry, and dynamic agent information needed for behavioral planning evaluation
• Developing message schemas and interface specifications for the Evaluation Gateway, including cryptographic hashing methods for data integrity verification
• Ensuring compatibility of state representations with industry standards and common AD stack architectures (both end-to-end and modular)

U.S. Citizen Preferred

Key responsibilities will include but are not limited to:

The above responsibilities are detailed in the job description.

Qualifications:

• MS or (BS + 2 years of experience) in Computer Science, Robotics, AI/Machine Learning, or related engineering fields
• Strong programming experience in Python and C++, with familiarity with AI/ML frameworks (TensorFlow, PyTorch, etc.)
• Experience with autonomous vehicle simulation environments (CARLA, SUMO, or similar)
• Knowledge of autonomous vehicle systems architecture and behavioral planning concepts
• Experience with ROS 2 on Linux systems
• Experience with version control software and workflow (Git/GitHub/GitLab)
• Understanding of data modeling principles and validation methodologies
• Familiarity with database design and management for storing and querying structured scenario data