AbbVie is looking to solve serious health issues today and address the medical challenges of tomorrow by discovering and delivering innovative medicines and solutions, and this internship is focused on developing and implementing AI-driven tools for content authoring and quality control review of regulatory documents.
Requirements
- Familiarity with data analysis and programming (e.g., Python or R).
- Previous experience with natural language processing (NLP) or generative AI models.
- Exposure to regulatory science, pharmaceutical industry practices, or biomedical research.
- Ability to interpret scientific literature and regulatory guidance documents.
- Strong interest in pharmaceutical sciences, regulatory science, or healthcare data.
- Currently enrolled in a Bachelor’s in Data Science, Computer Science, Bioinformatics, Biomedical Engineering, or a related field
Responsibilities
- Collaborate with scientists and regulatory professionals to understand the requirements and structure of regulatory documents.
- Assist in developing and applying data science and GenAI models to automate content generation and QC processes.
- Curate, clean, and structure data to train and validate AI models for document authoring and review.
- Evaluate and implement natural language processing (NLP) techniques for text summarization, information extraction, and document comparison.
- Participate in the development and validation of automated QC tools for identifying inconsistencies, errors, and gaps in regulatory submissions.
- Present findings, tools, and recommendations to cross-functional teams and document results in clear, concise reports
Other
- Must be enrolled in university for at least one semester following the internship
- Expected graduation date between December 2026 – June 2027
- Effective communication skills and ability to work collaboratively in a team environment
- Currently enrolled in a Bachelor’s in Data Science, Computer Science, Bioinformatics, Biomedical Engineering, or a related field
- Equal Opportunity Employer/Veterans/Disabled
