PREP0004857 Autonomous Systems Researcher

Autonomous Systems Researcher

Project Description:

Performance Evaluation of AI Capabilities in Autonomous and Human-Robot Interaction (HRI) Systems. To support the National Institute of Standards and Technology’s Measurement Science for Manufacturing Robotics and Autonomous Systems (MSRAS) Program. The focus of this role is to advance standard test methods, metrics, and evaluation tools for artificial intelligence, machine learning, and advanced autonomy within human-robot environments, ensuring these systems operate with transparent, verifiable, and securely integrated decision-making frameworks.

Key Responsibilities: 

• Conduct state-of-the-art measurement science research in robotics, advanced autonomy, and artificial intelligence systems 
• Utilize deep learning, large language models (LLMs), reinforcement learning, and unsupervised machine learning techniques to enhance robot capabilities, human objective prediction, and decision-making architectures
• Develop verification methods, transparent evaluation frameworks, and performance metrics to ensure robotic AI systems and automated sorting or ranking methodologies are inspectable and risk-aware
• Implement advanced filtering techniques and symbolic spatial relation models to optimize tracking, navigation, and behavioral classification in highly dynamic environments
• Program, simulate, and validate physical and simulated autonomous systems using a variety of modern software, libraries, and probabilistic frameworks
• Help develop standards, benchmark scenarios, and performance metrics for human-robot interaction (HRI), autonomous systems, and cooperative robotics integrated into complex environments
• Develop test apparatuses, digital twins, and virtual/physical testbeds using 3D rendering, CAD, and sensor fusion tools to validate repeatability and reproducibility. 
• Collaborate with interdisciplinary teams to design and optimize systems while publishing peer-reviewed research results in high-impact journals and international conferences

Desired Qualifications: 

• U.S. Citizen Preferred
• Ph.D. degree in Computer Science, Information and Computer Science, Modeling and Simulation Engineering, Aerospace Engineering, or a closely related quantitative field
• Experience in: Deep learning models, large language models (LLMs), unsupervised clustering, autoencoders, probabilistic programming, AI planning tools, human-robot interaction, activity/intent recognition, path planning algorithms, state estimation, algorithmic auditing, explainable AI frameworks, usability studies, human-in-the-loop validation, risk-aware system design, 3D rendering, discrete event simulation, motion capture data integration, and inertial navigation system architectures
• Proficiency in: Python, C/C++, Java, MATLAB, exposure to functional or specialized languages (e.g., Common Lisp), PyTorch, TensorFlow, ROS, OpenGL, probabilistic graphical libraries, LaTeX, 3D CAD modeling, 3D Printing workflow management, and modern developer tooling

Other Details:

• Full-time: the participant is expected to work 40 hours a week
• Location: the participant will work at the NIST Gaithersburg Campus.
• Duration: this is expected to be a one-year position. Extensions are sometimes granted depending on the availability of funds.