Multiple PhD student and postdoctoral researcher positions are available in the AI for Materials group of Dr. Kangming Li at King Abdullah University of Science and Technology (KAUST). The group develops machine-learning methods and computational modelling workflows for autonomous computational and experimental materials research.
Research topics include:
* Machine-learning methods for materials science: out-of-distribution generalization, uncertainty quantification, active learning, generative modelling, and dataset quality assessment
* AI-accelerated atomistic modelling: automated DFT/MD/MC workflows, machine-learning interatomic potentials, dataset curation, and workflow orchestration
* Integration of computational and experimental data: transfer learning, multimodal learning, descriptor design, automated spectral-data analysis, and LLM-based materials design
Application areas include structural materials, catalysis, batteries, metal-organic frameworks, solar cells, and related materials systems.
Appointment details:
Postdoctoral researchers:
* Initial appointment for one year, renewable up to five years
* Competitive tax-free salary, starting from USD 50,000/year
* Benefits include free on-campus housing, medical insurance including dependents, support for children’s education, an annual round-trip ticket to the home country, and relocation support
PhD students:
* Fully funded PhD positions through the KAUST Fellowship. Total fellowship value approximately USD 70,000-80,000/year, including tuition, housing, medical insurance, and relocation/travel support
* Tax-free annual stipend of USD 25,000-30,000
The start date is flexible, with preference for an early start.
Candidates should have a background in materials science, chemistry, physics, applied mathematics, computer science, or a related field. Strong computational skills are expected, including experience with programming and/or high-performance computing. Experience with atomistic modelling and/or machine learning is highly desirable but not strictly required.
How to apply:
Please send a single PDF file to [email protected] with the subject line: “Postdoc/PhD Position Inquiry”. The PDF should include:
* CV
* Cover letter describing relevant computational experience and research interests
* Names and contact information of three references
* Academic transcripts for PhD applicants