Posted on 2026/04/15
Postdoctoral Associate - Advanced Reasoning in Large Language Models
Mohamed bin Zayed University of Artificial Intelligence
United Arab Emirates
Job description
Mohamed bin Zayed University of Artificial Intelligence: Academic
Appointments: School of Computing: Machine Learning
Description
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) is
the world’s first AI-focused university. Founded in 2019, MBZUAI is
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 world’s top 25 by CSRankings for
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 to develop proprietary, domain-specific Large Language
Models (LLMs) for the Oil and Gas industry.
These models will form
the core of an agentic system designed to dramatically reduce
decision-making time and enhance operations for end-users.
This position will focus on fundamentally improving the complex
reasoning capabilities of LLMs.
The Postdoctoral Associate will be
responsible for researching, developing, and implementing advanced
techniques to create models that can solve complex mathematical,
physics, and reasoning problems specific to the energy sector.
This
is a unique opportunity to work at the intersection of foundational
AI research and high-impact industrial application, under the
supervision of Prof.
Martin Takac and Prof.
Salem Lahlou.
Key Responsibilities:
• Design and implement advanced training and fine-tuning
methodologies ( Reinforcement Learning from Human Feedback,
Reinforcement Fine Tuning, Mixture-of-Experts , etc.) to enhance
the reasoning capabilities of LLMs.
• Conduct domain adaptation of open-source models using
proprietary data from the Oil and Gas sector.
• Implement and refine Retrieval-Augmented Generation (RAG)
techniques and integrate knowledge graphs to improve model accuracy
and contextual understanding.
• Conduct rigorous evaluation of models on both domain-specific
datasets (MCQ, QA) and standard industry benchmarks ( MMLU, GPQA,
MATH, GSM8K, etc. ).
• Ensure models are safe and helpful, preventing the generation
of harmful content or sensitive information.
• Stay up-to-date with the latest literature on LLM reasoning,
developing and implementing novel ideas.
• Pioneer innovative techniques and original ideas aimed at
fundamentally improving the reasoning abilities of large language
models, both for project-specific applications and for the wider
research community.
• Publish research findings in top-tier AI and NLP conferences
and journals.
• Work with and mentor graduate students involved in the
project.
Qualifications
A Ph.D. in Computer Science, Machine Learning, Artificial
Intelligence, or a related field with a strong focus on Natural
Language Processing or Large Language Models.
Minimum:
• A strong track record of relevant publications in leading AI,
Machine Learning, or NLP conferences/journals.
• Hands-on experience in training, fine-tuning, and evaluating
large language models .
• Proficiency in deep learning frameworks such as PyTorch or
TensorFlow.
• Solid understanding of LLM architectures and advanced training
techniques (e.g., RLHF, RAG, Mixture-of-Experts).
• Strong programming skills in Python.
• Excellent communication and collaboration skills.
Preferred:
• Demonstrated research experience in LLM reasoning, mathematical
problem-solving, or agentic AI systems .
• Familiarity with knowledge graphs, graph-augmented language
models, or preference-based optimization methods.
• Experience working on collaborative, multi-disciplinary
research projects, especially with industry partners.
• Experience mentoring junior researchers or students.
What we offer:
• Opportunity to work on a high-impact, industry-relevant
research project with a major energy partner.
• A stimulating research environment at MBZUAI with leading
experts in AI.
• Competitive compensation and benefits package aligned with
top-tier academic markets.
• Significant opportunities for professional development and
travel to major conferences.
• A one-year appointment with the possibility of extension based
on performance and project needs.
Application Instructions
Interested candidates should submit the following documents:
Cover letter.
Current Curriculum Vitae (C.
V.).
-
A link to your Google Scholar profile.
A document (1-2 pages) describing two novel ideas or research
directions you would like to pursue to improve the reasoning
abilities of LLMs, including their potential application to the
energy sector.
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.
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