Autonomous Robotics AI Research Fellow

Johns Hopkins University; Gaithersburg (MD); On-site; USD 82,000 - 89,000; Full time

Job summary

Johns Hopkins University in Gaithersburg, MD seeks a PREP Research Associate to advance AI evaluation in autonomous and human-robot interaction systems, collaborating within NIST MSRAS. The role emphasizes measurement science, verification methods, and scalable testing across dynamic robotic environments.

The candidate will apply deep learning, reinforcement and unsupervised learning, develop benchmarks, and publish findings while working with interdisciplinary teams over a 1-year appointment

Qualifications

• Ph.D. or equivalent in natural sciences, engineering, or related fields.
• Strong experimental skills and innovative thinking.
• Ability to work both independently and collaboratively.
• Effective written and oral communication skills.

Responsibilities

• Conduct state-of-the-art research in robotics, autonomy, and AI systems.
• Develop verification methods, evaluation frameworks and metrics for HRI and robotic AI systems.
• Implement filtering and symbolic spatial relation models for tracking and navigation in dynamic environments.
• Collaborate with interdisciplinary teams and publish results in peer-reviewed venues.

Skills

Deep learning

LLMs

Reinforcement learning

Unsupervised learning

Experimental skills

Independent work

Written & verbal communication

Education

Ph.D. or equivalent in natural sciences, engineering, or related fields

Tools

CAD

3D rendering

Sensor fusion tools

Job description

Johns Hopkins University in Gaithersburg, MD seeks a PREP Research Associate to advance AI evaluation in autonomous and human-robot interaction systems, collaborating within NIST MSRAS. The role emphasizes measurement science, verification methods, and scalable testing across dynamic robotic environments.

The candidate will apply deep learning, reinforcement and unsupervised learning, develop benchmarks, and publish findings while working with interdisciplinary teams over a 1-year appointment