Post-Doctoral Associate in Robot Learning & Control Laboratory in the Division of Engineering Dr. Fares Abu-Dakka

The Robot Learning & Control Lab (REAL Lab) at NYU Abu Dhabi is seeking an outstanding Post-Doctoral Associate to contribute to cutting-edge research in robot intelligence machine learning and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning control and AI for physical systems.

The postdoc will work on projects focusing on one or more of the following:

• Robot Learning & Autonomy Developing algorithms that allow robots to learn (via exploration or imitation) from interaction adapt to new tasks and generalize across environments.
• Dexterous Manipulation Advancing robotic grasping in-hand manipulation and adaptable object handling in complex real-world scenarios including those involving deformable objects and uncertain conditions..
• Semantic Navigation & Mapping Designing solutions for robot navigation for Mobile Manipulators that integrate environmental semantics and spatial reasoning.
• AI for Physical Systems Leveraging machine learning and AI to improve performance safety and adaptability of robots autonomous vehicles and other intelligent machines.
• Safe and Certified Control for manipulation: Designing control algorithms that ensure passivity Lyapunov stability and safety for human-robot collaboration.

Qualifications:

Applicants must have a PhD in Robotics Control Engineering Machine Learning AI Mechanical or Electrical Engineering or a closely related field.

• Strong focus on robot manipulation learning & control and differential geometry is a plus.
• Knowledge of safe control methods including Lyapunov stability barrier functions and certified learning frameworks.
• Hands-on experience with robotic manipulators (preferebly Franka Emika R3 robots) and real-world experimentation.
• Demonstrate a high degree of self-motivation research-oriented thinking and a drive to operationalize robotic systems for real-world tasks.
• Strong publication record in top-tier venues: ICRA IROS RA-L T-RO IJRR CoRL NeurIPS RSS CDC TAC.
• Proficiency in Python C ROS and machine learning frameworks such as PyTorch or TensorFlow.
• Excellent communication and collaboration skills with the ability to work effectively in an interdisciplinary research environment.

For consideration applicants need to submit a cover letter curriculum vitae with full publication list statement of research interests a transcript and two letters of reference all in PDF format. If you have any questions please email Prof. Fares Abu-Dakka at

The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled.

Position Details

Duration: 2 years with the possibility of renewal based on performance and project needs.

Location: NYU Abu Dhabi a world-class research institution offering a collaborative interdisciplinary research environment.

About NYUAD:

NYU Abu Dhabi is a degree-granting research university with a fully integrated liberal arts and science undergraduate program in the Arts Sciences Social Sciences Humanities and Engineering. NYU Abu Dhabi NYU New York and NYU Shanghai form the backbone of NYUs global network university an interconnected network of portal campuses and academic centers across six continents that enable seamless international mobility of students and faculty in their pursuit of academic and scholarly activity. This global university represents a transformative shift in higher education one in which the intellectual and creative endeavors of academia are shaped and examined through an international and multicultural perspective. As a major intellectual hub at the crossroads of the Arab world NYUAD serves as a center for scholarly thought advanced research knowledge creation and sharing through its academic research and creative activities.

EOE/AA/Minorities/Females/Vet/Disabled/SexualOrientation/Gender Identity Employer

UAE Nationals are encouraged to apply