Post-Doctoral Associate in the Division of Engineering - Dr Muhammad Umar Niazi

Nyu-Abu Dhabi • San Francisco, CA

82d

About The Position

The Division of Engineering at New York University Abu Dhabi seeks to recruit a motivated post-doctoral associate with a strong background in control systems and machine learning to join the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins using physics-informed learning approaches, with specific applications to intelligent transportation systems (ITS). In particular, the successful candidate will conduct cutting-edge research in: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design Creating and validating digital twin architectures that incorporate physical laws and constraints Applying digital twin technology to ITS applications such as traffic management, vehicle routing, and infrastructure monitoring, as well as connected autonomous vehicles Integrating multi-modal sensor data with physics-based models Developing robust and adaptive methods for real-time parameter and state estimation Implementing machine learning approaches that preserve physical constraints while handling ITS-specific challenges.

Requirements

• Ph.D. in Electrical Engineering, Computer Science, Applied Mathematics, or related fields.
• Strong background in control systems, machine learning, and scientific computing.
• Programming proficiency and experience with simulation tools.
• Excellent publication record in peer-reviewed journals.
• Strong written and verbal communication skills.

Responsibilities

• Develop physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design.
• Create and validate digital twin architectures that incorporate physical laws and constraints.
• Apply digital twin technology to ITS applications such as traffic management, vehicle routing, and infrastructure monitoring.
• Integrate multi-modal sensor data with physics-based models.
• Develop robust and adaptive methods for real-time parameter and state estimation.
• Implement machine learning approaches that preserve physical constraints while handling ITS-specific challenges.

Benefits

• Competitive salary package.
• Generous housing allowance.
• Transportation allowance.
• Travel allowance for conferences and research activities.
• Educational subsidies for children.
• Comprehensive medical insurance coverage.
• Relocation assistance package.
• Access to state-of-the-art computing resources and research equipment.
• Opportunities for professional development and networking.
• Collaborative and innovative research environment.

What This Job Offers

• Career Level: Entry Level
• Industry: Web Search Portals, Libraries, Archives, and Other Information Services
• Education Level: Ph.D. or professional degree