Postdoctoral Researcher in Artificial Intelligence, Computer Vision, and Multimodal Vision-Language Models at King Fahd University of Petroleum & Minerals King Fahd University of Petroleum & Minerals in Saudi Arabia

King Fahd University of Petroleum & Minerals (KFUPM) is seeking exceptional Postdoctoral Researchers to join the BRAIN Lab, led by Assistant Professor Muzammil Behzad, in advancing the frontiers of Artificial Intelligence and Multimodal Computing. KFUPM is ranked #67 worldwide (QS Rankings) and offers a world-class research ecosystem integrating AI technologies to address complex real-world challenges.

Highlighted research areas include Vision-Language Models (VLMs) for next-generation multimodal AI, Generative AI (GANs, diffusion models, synthetic data generation), AI for Healthcare (medical imaging, clinical decision support, digital health), Affective Computing (emotion recognition from facial expressions, gestures, and human behavior), and Human-Computer Interaction (intelligent interfaces and adaptive systems).

The postdoctoral position provides an annual salary of USD 48,000, a housing allowance equivalent to three months’ salary, access to state-of-the-art campus facilities and a private beach, campus medical services, and 30 days of paid annual leave. The university fosters a collaborative, innovative academic environment and supports postdocs through fellowships and research center funding.

Applicants must have a Ph.D. in a related field (such as AI, Computer Science, or a closely aligned discipline) and must not have received any grades of D, E, or F throughout their BS, MS, and Ph.D. studies. Additional competencies may be required depending on the research center or project. The application process requires filling out a specific online form, and only shortlisted candidates will be contacted for interviews. For more information, visit the provided links or contact Dr. Muzammil Behzad directly.

Keywords: Artificial Intelligence, Computer Vision, Generative AI, Multimodal Vision-Language Models, AI for Healthcare, Affective Computing, Human-Computer Interaction.