AbbVie is looking to create and develop artificial intelligence (AI) and machine learning (ML) engines for pharmaceutical development projects to improve efficiency and decision-making.
Requirements
- Currently enrolled in university, pursuing a PhD in computer or data science (or other related field) with a focus on artificial intelligence, machine learning, computational linguistics, natural language processing, or equivalent.
- Demonstrated knowledge and experience in the application of artificial intelligence and machine learning in professional industries.
- Familiarity with pharmaceutical development preferred.
Responsibilities
- Evaluating various software configurations against pharmaceutical regulatory requirements to determine best options based on pre-established acceptance parameters.
- Classifying incoming information from different external sources into specific categories, providing meaningful summaries, and identifying the appropriate subject matter experts with automated communications.
- Designing a tool to screen and summarize available financial information and invoices of pre-defined work packages to generate an accurate estimate or prediction of costs for future work.
- Creating a dynamic tool to automate resource planning and work package projections to predict time and financial efficiencies, allowing real-time adjustment of resources, task re-prioritization and/or outsourcing opportunities.
- Following a dynamic regulatory environment to maintain quality standards, where applicable.
- Effectively managing local and global interfaces across impacted stakeholders, including R&D and IT functions.
- Influencing mid- and long-term strategic focus areas while articulating new opportunities for AI/ML applications within the business.
Other
- Must be enrolled in university for at least one semester following the internship.
- Strong written and verbal communication skills.
- Strong critical thinking and collaboration skills.
- Skilled in managing tasks efficiently with an emphasis on prioritization and productivity.
- Demonstrates reliability, responsibility, and dedication in all aspects of work.
- Expected graduation date between December 2026 – July 2027.
