Postdoctoral Associate - Personalization & Recommendation

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).

I nvestigate 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 hallucin ation s 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.

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 .

with A/B testing and online evaluation of recommendation systems.

Familiarity with economic principles related to pricing and upselling.

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.

Interested candidates should submit the following: Cover letter Current Curriculum Vitae (C.V.) Link to Google Scholar Statement of research vision and interests (optional) Applications will be reviewed on a rolling basis, and the position will remain open until filled.

For more information or to apply, please visit MBZUAI Careers or contact us directly at NLP.IndustryProject@mbzuai.ac.ae