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Posted 1 month ago

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Materials science intern

SingaporeRemoteFull-time

AI Summary

Materials science intern translates complex semiconductor process knowledge into standardized, reusable entries and helps build a knowledge graph. Collaborates cross-functionally to enhance data quality and presentation.

About this role

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.

    • Skills

    BEOLBilingual Knowledge ContentComparison MatricesDatabasesData CurationData QualityDecision TreesDefect AnalysisFEOLFlowchartsInformation ArchitectureKnowledge GraphsLLM ApplicationsPatent Text AnalysisProcess CardsProcess Control PointsProcess FlowProcess OptimizationRAG (retrieval-augmented Generation)Semiconductor Processes

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