Postdoctoral Associate - Personalization & Recommendation
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Job Description
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) is the worlds first AI focused university. Founded in 2019 MBZUAI started as a research-oriented graduate level university that has grown to host over 80 world-class faculty over 330 graduate-level students and is already ranked in the worlds top 25 byCSRankingsfor AI-related fields. Located in Abu Dhabi the university aims to become a global leader in AI education and research by providing cutting-edge programs in Artificial Intelligence empowering students to shape the future of technology. MBZUAI is committed to fostering innovation collaboration and ethical practices in AI to address global challenges.
About the role:
This project is a collaboration between MBZUAI and a Major Industry Partner in the UAE that aims to create a state-of-the-art Conversational Booking Agent. The agent will integrate with existing company systems engage users naturally and effectively in English (with future expansion to Arabic) ensure safety and reliability and provide personalized recommendations. This position focuses on the core natural language processing and developing conversational capabilities of the agent.
The Postdoctoral Research Scientist in Recommendation & Personalization will focus on finding optimal offers based on user behaviour. This involves leveraging user interaction history building user profiles integrating external knowledge sources and working with techniques like knowledge graphs RAG (Retrieval-Augmented Generation) grounding information for accuracy and exploring the use of causal reasoning to offer timely and relevant suggestions that enhance user value and align with business objectives.
Key Responsibilities:
- Design and implement algorithms for personalized product/service recommendations and upselling within a conversational context.
- Explore and utilize techniques like Knowledge Graphs and Retrieval-Augmented Generation (RAG) to ground recommendations and provide contextually relevant information (e.g. visa requirements local attractions).
- Investigate the use of counter-factual reasoning or causality frameworks to understand why certain recommendations are effective and to improve strategy.
- Design an infrastructure to continually learn from new data to improve recommendations made to the user.
- Integrate recommendations with the NLP engine mitigate hallucinations and ensure the information provided is accurate.
- Work with data scientists and engineers to integrate recommendation modules with user data sources and backend systems (e.g. pricing engines loyalty programs).
- Design and conduct experiments to evaluate the effectiveness of different recommendation and upselling strategies.
- Publish research findings in top-tier conferences and journals.
PhD in Computer Science Machine Learning or a related field with a focus on Recommender Systems Personalization Information Retrieval or Data Mining.
Minimum:
- Strong understanding of machine learning techniques relevant to personalization and user modelling.
- Hands-on experience with Retrieval-Augmented Generation (RAG) models including integrating external knowledge sources to improve model performance.
- Experience in developing and evaluating recommendation systems.
- Familiarity with techniques like collaborative filtering content-based filtering sequence modeling and reinforcement learning for recommendations.
- Proficiency in working with deep learning frameworks.
- Expert knowledge in latest research on recommender systems and personalization.
- Track record of relevant publications in leading NLP/ML conferences or journals.
- Excellent communication and collaboration skills.
Preferred:
- Experience with applying recommendations in conversational AI or chatbot settings.
- Knowledge of causal inference or counter-factual reasoning techniques.
- Experience with A/B testing and online evaluation of recommendation systems.
- Familiarity with economic principles related to pricing and upselling.
- Experience working in collaborative multi-disciplinary research projects.
What we offer:
- Opportunity to work on a high-impact industry-relevant research project.
- A stimulating research environment at MBZUAI with leading experts in AI.
- Competitive compensation and benefit package aligned with top-tier academic markets.
- Opportunities for professional development and conference travel.
Required Experience:
IC
Employment Type
Full Time
