The University of Dubai is offering exciting research positions as part of a 3-year RDI project focused on LiFi, optical wireless communications, and lightweight AI/ML for adaptive systems. The project is a collaboration with leading experts Prof. Harald Haas and Prof. Boon Ooi, and aims to advance solar-powered optical wireless communication platforms and AI-enabled adaptive systems. Open roles include a full-time Postdoctoral Fellow position in Optoelectronic Receiver Design and a part-time AI Scientist position specializing in lightweight machine learning for SLIPT control and adaptive optical wireless systems. The Postdoctoral Fellow will lead R&D on dual-mode photodetector arrays, hardware prototyping, and system integration, while the AI Scientist will focus on developing and optimizing ML models for adaptive modulation and environment-aware prediction. Applicants for the Postdoctoral Fellow role should hold a PhD in Electrical Engineering, Photonics, Optoelectronics, Optical Communications, or a closely related field, with demonstrated expertise in photodetectors, receiver design, and experimental characterization. Strong lab skills, proficiency in Python or MATLAB, and a publication record are required. The AI Scientist role requires a PhD or MSc in Machine Learning, Computer Engineering, Data Science, or a related discipline, with hands-on experience in Python-based ML workflows and lightweight modeling techniques. Both positions are funded by the University of Dubai's College of Engineering and IT. The application deadline is February 25, 2026. Interested candidates should apply via the official University of Dubai career links or contact [email protected] for further information. This is an excellent opportunity to work on cutting-edge research in LiFi, optical wireless communications, and AI-driven adaptive systems in Dubai, UAE.

The University of Dubai is seeking candidates for two research positions as part of a 3-year RDI research project focused on LiFi, optical wireless communications, and lightweight AI/ML for adaptive systems. The project is a collaboration involving Prof. Diana W. Dawoud (University of Surrey), Prof. Harald Haas, and Prof. Boon Ooi, and aims to advance the state-of-the-art in optoelectronic receiver design and AI-driven system adaptation. Postdoctoral Fellow (Optoelectronic Receiver Design for Solar-Powered LiFi / Dual-Mode Photodetectors): The postdoctoral fellow will lead R&D on optoelectronic receiver hardware for a solar-powered optical wireless communication platform. Responsibilities include designing and prototyping a dual-mode photodetector array, developing front-end electronics, and establishing laboratory workflows for electro-optical characterization. The fellow will also support system integration, collaborate with the AI/software team, and contribute to technical reporting and publications. Applicants must have a PhD in Electrical Engineering, Photonics, Optoelectronics, Optical Communications, or a related field, with hands-on experience in photodetectors, lab instrumentation, and data analysis using Python or MATLAB. AI Scientist (Lightweight ML for SLIPT Control and Adaptive Optical Wireless Systems): The AI Scientist will provide part-time, specialized support for the design, training, and optimization of lightweight machine learning models enabling SLIPT control, adaptive modulation, and environment-aware prediction. The role involves dataset preprocessing, model prototyping, benchmarking, and collaboration with hardware teams. Candidates should have a PhD or MSc in Machine Learning, Computer Engineering, Data Science, or a related discipline, with strong Python-based ML skills and experience in lightweight modeling techniques. Both positions are funded as part of the RDI project, with the postdoctoral fellow being a full-time role and the AI Scientist a part-time, project-based position. The application deadline is February 25, 2026. For more information or to apply, candidates should use the University of Dubai career portal links or contact Prof. Diana W. Dawoud via LinkedIn. The project offers an excellent opportunity to work at the intersection of optical wireless communications, AI, and hardware systems, with collaboration across leading academic and industry partners.