Research Associate – AI & Data Science Specialist for Airline Operations Optimization

University of Doha for Science and Technology (UDST), officially established by Emiri Decision No. 13 of 2022, is Qatar’s first national applied university and the country’s premier destination for academic, technical, and professional education. With more than 8,000 students and 700 staff, UDST offers over 70 applied bachelor’s, master’s, diploma, and certificate programs across its five colleges: Business, Computing & Information Technology, Engineering & Technology, Health Sciences, and General Education. In addition, UDST houses specialized training centers that serve both individuals and industry.

UDST is recognized for its student-centered learning, cutting-edge facilities, and applied, experiential approach. Our world-class faculty and researchers leverage innovative learning technologies and foster partnerships with global institutions to develop highly skilled graduates who contribute directly to Qatar’s knowledge-based economy and support the goals of Qatar National Vision 2030. As a growing hub for research and innovation, UDST is home to advanced projects that bridge academia and industry.

We are seeking a highly motivated Research Associate to join a collaborative project between University of Doha for Science and Technology (UDST) and Qatar Airways. The ideal candidate will have a strong background in data analysis, artificial intelligence, operations research, and optimization techniques, with a particular emphasis on Data-driven approaches.

• Data Preparation and Analysis: Collect, preprocess, and analyze large datasets related to flight operations and other pertinent areas to inform model development and validation. This includes handling missing or incorrect data, identifying patterns, and ensuring data quality.
• Model Development: Design and implement predictive models to forecast crew requirements based on historical and real-time operational data. Account for uncertainty due to disruptions and unforeseen events.
• Optimization Algorithms: Develop and apply operations research methodologies and reinforcement learning algorithms to dynamically generate optimal solutions that enhance operational efficiency and adhere to all relevant constraints.
• Simulation and Testing: Create simulation environments to test and validate the performance of developed models and algorithms under various operational scenarios and disruptions.
• Regulatory Compliance Integration: Ensure that all models and optimization workflows comply with aviation regulations, including duty-time limits, rest periods, qualification rules, and safety standards. Collaborate with compliance officers to embed these rules effectively in the system logic.
• Collaboration: Work closely with interdisciplinary teams, including data scientists, operations researchers, and airline operations personnel, to ensure the practical applicability of developed solutions.
• Documentation and Reporting: Prepare comprehensive documentation of methodologies, algorithms, and findings. Present research outcomes to stakeholders and contribute to academic publications

Qualifications:

• Educational Background: a Ph.D. Computer, Operations Research, Applied Mathematics, or a related field  OR a Master degree in Computer science with a minimum of 5 years of experience in projects involving Data Science, Optimization and AI.
• Technical Expertise: Proficiency in data analysis, machine learning, and operations research techniques. Experience with predictive modeling and optimization algorithms such as Meta-heuristics is essential. Mastery of reinforcement learning (RL) is a plus.
• Programming Skills: Strong programming skills in languages such as Python or Rust or R. Familiarity with machine learning libraries and frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch) is a must.
• Analytical Skills: Demonstrated ability to analyze complex datasets and develop data-driven solutions.
• Communication Skills: Excellent written and verbal communication skills, with the ability to convey complex technical concepts to non-technical audiences.
• Team Collaboration: Proven experience working in collaborative team environments and managing multiple tasks effectively.

Preferred Qualifications:

• Experience in airline operations, or related domains.
• Familiarity with regulatory frameworks governing aviation operations.