Postdoctoral Researcher - Generative and Agentic AI
Overview
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 9,000 students and 700 staff, UDST offers over 70 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. UDST Center of Excellence – Artificial Intelligence and Innovation is dedicated to advancing cutting‑edge AI research and developing practical solutions that tackle real‑world challenges. Our mission is to drive scientific progress and technological innovation in intelligent systems, contributing to Qatar's transition to a knowledge‑based economy in line with Qatar National Vision 2030.
The Position
The Center is seeking an outstanding Postdoctoral Researcher to join a team of faculty, post‑doctoral researchers, programmers, and students. This role focuses on conducting advanced research in AI, with emphasis on Large Language Models (LLMs), generative AI, and agentic AI. You will design and evaluate innovative AI architectures, develop agent‑based and generative tools, and contribute to interdisciplinary research efforts. This is an excellent opportunity to work at the forefront of AI research while contributing to Qatar's knowledge‑based economy.
Key Responsibilities- Conduct advanced research in AI, focusing on LLMs, generative AI, and agentic AI
- Design and evaluate innovative AI architectures and agent‑based frameworks
- Develop research prototypes, tools, and datasets that advance the state‑of‑the‑art in AI
- Publish research findings in top‑tier peer‑reviewed conferences and journals
- Lead and contribute to high‑impact research projects aligned with the Center's priorities
- Ensure reproducibility and documentation of research through best practices in code and data management
- Collaborate with internal and external stakeholders on interdisciplinary research initiatives
- Contribute to research proposals and external funding applications to support the Center's growth
- Mentor junior researchers, graduate students, and research assistants
- PhD in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field
- Demonstrated research experience in artificial intelligence, with focus on LLMs and agentic AI
- Strong publication record in peer‑reviewed journals and top‑tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, and AAAI)
- Expertise in deep learning frameworks (PyTorch, Tensor Flow) and experience with transformers and large models.
- Strong background in machine learning, natural language processing, or generative AI
- Experience with evaluating AI models, benchmark design, and assessment methodologies
- Experience with retrieval‑augmented generation (RAG) and LLM‑based applications
- Proven ability to conduct independent research and contribute to collaborative research teams
- Excellent analytical, problem‑solving, and communication skills, including research presentations and technical writing
- Proficiency with version control systems (Git) and reproducible research practices
- Experience with computational resources and high‑performance computing environments
- Fluency in written and spoken English
- Experience with reinforcement learning, multi‑agent systems, or autonomous systems
- Familiarity with AI safety, alignment, fairness, bias detection, or…
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