Kangming Li

This postdoctoral position at King Abdullah University of Science and Technology (KAUST) is focused on the application of artificial intelligence (AI) and machine learning to advanced materials design. The successful candidate will join the Physical Science and Engineering Division, working on projects that leverage machine learning and high-throughput first-principles calculations to accelerate the discovery of new materials. The research sits at the intersection of computational science, materials engineering, and AI, with main directions including the development of machine learning methods and models, out-of-distribution generalization, uncertainty quantification, active learning, generative modeling, and dataset quality assessment. Additional research areas involve automating atomistic modeling workflows, developing ML methods for workflow orchestration, dataset curation, and the creation of ML interatomic potentials. The integration of AI with computational and experimental approaches is also a key focus, including transfer learning, multimodal learning, descriptor design, and automated spectral data analysis. The ideal candidate will have a strong background in materials science, chemistry, physics, or a related field, and be comfortable with computational work such as coding and using high-performance computing resources. Experience with atomistic modeling techniques (DFT, MD, MC) and machine learning is preferred but not strictly required. The position is based in Thuwal, Makkah, Saudi Arabia, and offers the opportunity to work in a cutting-edge research environment at KAUST. The application deadline is January 1, 2026. For more information or to apply, candidates should contact Dr. Kangming Li at [email protected].