Post Doctoral Fellow

KHALIFA UNIVERSITY; United Arab Emirates; On-site; AED 120,000 - 200,000; Full time

Job summary

A leading academic institution in the UAE is seeking a highly motivated Post-doctoral Fellow to conduct advanced research on autonomous vehicles. The role involves developing efficient algorithms related to routing and planning while ensuring robust performance under uncertainty. Candidates should have hands-on experience in optimization, with a background in machine learning and robotics being advantageous. This position offers access to state-of-the-art facilities and a collaborative environment.

Qualifications

• Experience in the field of interest and optimization.
• Strong analytical skills for problem solving.
• Ability to work collaboratively within a team.

Responsibilities

• Perform cutting-edge research in autonomous vehicles.
• Develop algorithms with formal performance guarantees.
• Create robust planning and scheduling algorithms.

Skills

Technical hands-on experience in optimization

Knowledge in robust optimization

Background in machine learning

Background in robotics

Job description

Organisation/Company KHALIFA UNIVERSITY Research Field Computer science Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country United Arab Emirates Application Deadline 28 Feb 2026 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Position Overview

KU is seeking a highly motivated Post-doctoral Fellow to work on performing cutting-edge research in autonomous vehicles (AVs) with background in Theoretical Computer Science. The funded project includes two objectives: (O1) explore a class of novel, practically driven generalizations of classical routing and planning problems, such as TSP and UFP, with application to navigation and mission planning of autonomous vehicles. One such problem is the TSP problem with drones and legged robots for last‑mile logistics applications or environmental surveillance. In tackling these new problems, we seek to devise efficient routing algorithms with certifiable worst‑case performance guarantees. (O2) Developing a theoretical framework to synthesize multi‑agent controllers and coordination schemes that are robust against nondeterminism due to parameter uncertainty and disturbances. In view of real‑world nuances and sensing errors, we aim at developing robust planning and scheduling algorithms that tolerate noisy parameters. To ensure timely and high‑grade decision‑making, we seek to design polynomial‑time approximation algorithms that offer formal definite bounds on sub‑optimality or probably approximately correct (PAC)-style guarantees.

As part of the project, the researcher will have access to state-of-the-art research equipment and facilities at the Autonomous Vehicles Lab and will get an opportunity to work alongside researchers and graduate students from various backgrounds as part of a wider team.

Position Requirements

• Technical hands on experience and knowledge in the field of interest, optimization and some background in robust optimization.
• Optional: background in Machine learning
• Optional: background in robotics
• Adhere to the University's information security and confidentiality policies and procedures, and report breaches or other security risks accordingly
• Perform any other tasks assigned by the Line Manager

Should you require further assistance or if you face any issue with the online application, please feel to contact the Recruitment Team ([e-mail] ).