진학프로석·박사 채용 접수 플랫폼

About the Position

We are seeking a highly motivated postdoctoral researcher to join KAUST in the field of advanced materials design, with a focus on AI for Materials. The project will leverage machine learning and high-throughput first-principles calculations to accelerate materials discovery, working at the intersection of computational science, materials engineering, and artificial intelligence.

Main Research Directions includes:

Machine Learning Methods and Models

• Out-of-distribution generalization
• Uncertainty quantification, active learning
• Generative modeling
• Dataset quality assessment (redundancy, similarity, diversity)

AI-Accelerated Modeling

• Automating atomistic modeling workflows
• ML methods for workflow orchestration
• Dataset curation and ML interatomic potential development

AI and Computational-Experimental Integration

• Transfer learning, multimodal learning
• Descriptor design
• Automated spectral data analysis
• LLM-based design

Candidate Profile

Candidates should have a background in materials science, chemistry, physics, or a related field and be comfortable with computational work (coding, using HPC, etc.). Experience in atomistic modeling (DFT, MD, MC) and machine learning is preferred but not required.