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The Department of Mechanical Engineering at the American University of Sharjah (AUS) is inviting applications for a one-year postdoctoral research fellowship in autonomous driving systems and artificial intelligence, as part of a funded research project on lane-changing for autonomous vehicles.

• Lead the development and testing of hybrid trajectory prediction algorithms and high-level decision-making models.
• Design and implement advanced AI/ML/RL solutions for real-time driving behavior prediction and maneuver planning.
• Integrate models in simulation environments (e.g., CARLA, SUMO) and validate on real autonomous platforms.
• Publish high-quality journal papers and present at top-tier conferences.
• Supervise and collaborate with graduate research assistants and students.

• PhD in Mechanical/Mechatronics Engineering, Robotics, AI, or a related field.
• Awarded degree in 2020 or later from a reputable university.
• Strong publication record in areas such as autonomous vehicles, trajectory prediction, decision-making, reinforcement learning, or estimation theory.

• Deep understanding of the autonomous navigation stack: sensing, perception and localization, planning, and control.
• Proven experience designing decision-making systems for autonomous vehicles or ground robots.
• Deep understanding of decision paradigms: utility-based, rule-based, probabilistic, optimization, statistical learning, and reinforcement learning.
• Strong experience with behavior trees, state machines, and planning frameworks.
• Proficiency in MATLAB, C++, and Python; strong debugging and profiling skills.
• Hands‑on experience with ROS2, Docker, Git, and field robotics development on Linux systems.
• Solid grasp of software design patterns and scalable architecture principles.
• Excellent problem‑solving skills and the ability to navigate ambiguity in complex, dynamic systems.
• Strong communication and collaboration skills in interdisciplinary teams.
• Strong debugging and analytical skills, with experience validating systems in both simulated and real‑world environments.
• Hands‑on experience with mobile robots (e.g., Robotnik RB-Car) is an advantage.

• Interested applicants should fill out the form. The position is open until it is filled.
• AUS alumni are encouraged to apply. Applicants who do not meet specified requirements will not be shortlisted. Only shortlisted candidates will be contacted.
• AUS is an equal opportunity employer. We adhere to a policy of making employment decisions without regard to race, color, age, gender, religion, national origin, disability or marital status. Opportunities for employment are based solely upon one’s qualifications.