Materials science intern

We are seeking a detail-oriented candidate to structure and curate semiconductor process knowledge. You will translate complex technical content into standardised insights and collaborate cross-functionally to enhance data quality. Key Responsibilities: Distill and author standardized Process Skills from annotated data and patent texts, covering process objectives, flow steps, key parameters, control points, common defects, alternative solutions, and evolution paths. Participate in building a Semiconductor Process Knowledge Graph, mapping relationships among processes, materials, equipment, devices, and performance metrics. Assist in designing process retrieval and recommendation logic; optimize knowledge presentation formats (e.g., process cards, flowcharts, decision trees, comparison matrices). Work closely with product managers and algorithm teams to define knowledge-base schemas, quality standards, and update mechanisms. Track cutting-edge semiconductor process trends (e.g., Advanced Packaging, GAA transistors, novel memory devices, power semiconductors) and continuously enrich knowledge content. Requirements： Currently enrolled in a Bachelor’s degree or higher in Materials Science and Engineering (or a related field such as Electrical or Chemical Engineering), with a solid understanding of semiconductor materials and processes. Excellent technical writing and knowledge distillation skills; adept at abstracting complex process logic into clear, reusable, structured entries. Familiar with full semiconductor flows (FEOL/BEOL) or a specific segment (logic, memory, advanced packaging, compound semiconductors). Rigorous logical thinking; basic understanding of information architecture or databases. Knowledge of Knowledge Graphs, RAG (Retrieval-Augmented Generation), or LLM applications is preferred. Able to seamlessly process technical materials in both languages and produce bilingual knowledge content.