Content Analyst Intern (Materials Science)

Job Requirement

• Undergraduate or Master’s student in Materials Science, Chemistry, Physics, or a related field.
• Basic understanding of materials science principles and scientific research methods.
• Familiarity with data analysis tools (e.g., Excel, Python, or SQL) is a plus.
• Strong attention to detail and willingness to learn new tools and concepts.
• Good communication and teamwork skills.

Key Responsibilities

• Assist in researching and curating materials science content from diverse data sources, including scientific literature, databases, and patents.
• Support the integration, classification, and quality control of materials-related data.
• Learn to apply basic AI, ML, or data analysis techniques to extract insights and contribute to product development.
• Collaborate with cross-functional teams including data engineers and product managers to support project goals.
• Help maintain content accuracy and consistency aligned with materials science standards and ontologies.
• Participate in the exploration of new data trends, technologies, and tools in materials informatics.

Key Responsibilities

• Assist in researching and curating materials science content from diverse data sources, including scientific literature, databases, and patents.
• Support the integration, classification, and quality control of materials-related data.
• Learn to apply basic AI, ML, or data analysis techniques to extract insights and contribute to product development.
• Collaborate with cross-functional teams including data engineers and product managers to support project goals.
• Help maintain content accuracy and consistency aligned with materials science standards and ontologies.
• Participate in the exploration of new data trends, technologies, and tools in materials informatics.

Job Requirement

• Undergraduate or Master’s student in Materials Science, Chemistry, Physics, or a related field.
• Basic understanding of materials science principles and scientific research methods.
• Familiarity with data analysis tools (e.g., Excel, Python, or SQL) is a plus.
• Strong attention to detail and willingness to learn new tools and concepts.
• Good communication and teamwork skills.