Post-Doctoral Associate - Field Robotics, Control Theory, and Machine Intelligence - NYU

Post-Doctoral Associate – Field Robotics, Control Theory, and Machine Intelligence – NYU Abu Dhabi

This Post-Doctoral Associate position supports NYU Abu Dhabi's Electrical Engineering Program and the Center for Artificial Intelligence and Robotics. The role focuses on advancing autonomy in Field Robotic systems using nonlinear/optimal control, reinforcement learning, and data-driven modeling, with emphasis on marine robotics and opportunities across aerial and ground systems.

Job Details:
Country: UAE;
City:
Abu Dhabi;
Industry: Engineering;
Function:
Engineering;
Salary:  monthly (Market estimated);
Gender: Any;
Candidate Nationality:
Any;
Job Type: Full-time

• Conduct high-quality research at the intersection of control theory and machine intelligence
• Design, model, and optimize robotic systems, including marine, aerial, or ground platforms
• Integrate algorithms with embedded hardware and real-time systems
• Reproduce state-of-the‑art methods and benchmark against new approaches
• Design and implement outdoor experiments on real robotic platforms
• Prepare manuscripts for high‑impact journals and conferences
• Maintain high‑quality research code and ensure reproducibility
• Collaborate with NYUAD researchers, students, and global partners

• Doctoral degree in electrical, mechanical, naval, or aerospace engineering
• First‑author publications in peer‑reviewed journals
• Strong experience integrating hardware and software for robotic systems
• Demonstrated history of conducting field experiments with robotics
• Skilled in C/C , Python, real‑time embedded systems, and Git Hub code management
• Strong modeling, control, and machine learning foundation
• Ability to visualize experimental results and interpret system behavior
• Collaborative mindset with strong communication skills
• Self‑driven and eager to tackle multidisciplinary challenges

• Robot modeling and control
• Nonlinear and optimal control methods
• Reinforcement learning for robotics
• Data‑driven modeling and system identification
• Embedded programming (C/C ) and Python
• Real‑time robotics software integration
• Experimental robotics testing
• Research writing and documentation

• Opportunity to advance next‑generation field robotics in real experimental environments
• Work closely with world‑class researchers and AI/robotics collaborators
• Competitive tax‑free compensation with housing and travel benefits
• Access to advanced robotics facilities and outdoor testing environments
• High‑impact research visibility through publications and global collaborations
• Engage with NYU's international research ecosystem