Summary
United Arab Emirates University’s Big Data Analytics Center is seeking a postdoctoral researcher for AI, NLP, and large language model research and deployment. The role includes developing and evaluating models and architectures, building retrieval-augmented generation and knowledge graph frameworks, and supporting GPU infrastructure and MLOps workflows. The researcher will collaborate on projects and publications, contribute to proposals and training, and mentor junior researchers. A PhD in a related field, relevant research experience, a strong publication record, and proficiency in Python and major machine learning libraries are required.
The posting
As published on uaeu.ac.ae. Pulled from the employer's site and shown as they wrote it.
Job description
The Big Data Analytics Center (BIDAC) at the United Arab Emirates University (UAEU) is seeking an outstanding Postdoctoral Researcher to join its growing team focused on Artificial Intelligence, Natural Language Processing (NLP), and Large Language Model (LLM) research and deployment.
The selected candidate will contribute to high-impact research and applied projects aimed at developing domain-specific, efficient, and explainable LLMs tailored to the UAE’s strategic sectors such as education, healthcare, and digital government.
Working within one of the UAE’s leading AI research centers, the Postdoc will have access to state-of-the-art computing infrastructure, a multidisciplinary research environment, and collaboration opportunities with national and international partners.
This position is ideal for researchers who wish to advance the frontier of AI and NLP and translate research into real-world, deployable systems that drive digital transformation in the region.
Key Responsibilities:
• Conduct cutting-edge research in machine learning, NLP, and LLM optimization (fine-tuning, distillation, quantization).
• Develop and evaluate novel architectures, hybrid AI approaches, and explainable NLP systems.
• Design and implement retrieval-augmented generation (RAG) and knowledge graph-enhanced LLM frameworks.
• Collaborate with faculty, data engineers, and PhD/MSc students on research projects and publications.
• Publish high-quality papers in top-tier journals and conferences (e.g., NeurIPS, KDD, etc.).
• Support AI infrastructure setup, including GPU-based servers, data pipelines, and MLOps workflows.
• Contribute to grant writing, proposal preparation, and project documentation.
• Mentor junior researchers and contribute to training workshops or short courses.
Minimum qualification
- PhD in Computer Science, Artificial Intelligence, Data Science, or a closely related field.
- Demonstrated research experience in machine learning, NLP, or deep learning.
- Strong publication record in recognized AI/ML/NLP venues.
- Proficiency in Python and major ML/NLP libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers).
- Solid understanding of transformer architectures, embeddings, and attention mechanisms.
- Experience with data preprocessing, model training, and evaluation for text and multimodal datasets.
Preferred qualification
- Prior experience in LLM deployment on-premise or in secure, private environments.
- Experience with multilingual NLP, especially Arabic-English or low-resource language modeling.
- Proven track record of open-source contributions, patents, or applied AI projects.
- Background in knowledge graphs, semantic search, or hybrid symbolic-neural AI.
- Experience with cloud or HPC systems for large-scale model training (e.g., NVIDIA DGX, multi-GPU clusters).
- Exposure to prompt engineering, RLHF (Reinforcement Learning from Human Feedback), or evaluation of generative AI systems.
Department
Center For AI & Digital Innovation
College or division
Research Centers