2026 Summer Intern PhD Student - Engineering/Computational Scientist for Drug Product Development

Role Summary

2026 Summer Intern PhD Student - Engineering/Computational Scientist for Drug Product Development. Intern position within the Drug Product Development (DPD) department, focusing on leveraging predictive modeling and data science to advance drug development. 10-week guided research project with mentors, in New Brunswick, NJ, starting June 1, 2026.

Responsibilities

• Contribute to drug product development projects by designing and implementing computational models that analyze the effects of process variables and material properties on product attributes.
• Apply machine learning and artificial intelligence techniques to large datasets to drive insights for decision-making and mitigate product-related risks.
• Develop and test predictive models to understand key pharmaceutical unit operations for oral solid and parenteral dosage forms, including drug delivery devices.
• Collaborate with formulation, process development, and device engineering teams to improve product performance through data-driven insights.
• Communicate and present results at internal forums, including presentations to diverse audiences through data analysis and visualizations.

Qualifications

• Candidates must be currently enrolled in an accredited university program pursuing a Ph.D. in engineering, materials science, computational sciences, or related quantitative discipline, with expected graduation Fall 2026 to end of 2027.
• GPA of 3.0 or greater (include GPA on resume) and a two-page summary of current research.
• Demonstrated experience in computational modeling and/or data science applied to engineering or pharmaceutical challenges.
• Experience in programming languages such as Python, MATLAB, or R, with emphasis on data analysis and modeling (preferred).
• Experience developing data inputs for computational modeling (preferred).
• Knowledge of drug product development processes and pharmaceutical unit operations and/or medical devices (preferred).
• Strong communication skills; ability to present technical information to scientific and non-technical audiences.
• Ability to work independently and in a collaborative, multidisciplinary team.
• Authorized to work in the US for duration of employment; no visa sponsorship available.

Skills

• Computational modeling
• Machine learning and AI for large datasets
• Data analysis and visualization
• Collaboration and cross-functional communication

Education

• Ph.D. in engineering, materials science, computational sciences, or related quantitative discipline (current enrollment required).

Additional Requirements

• In-person internship in New Brunswick, NJ for ~10 weeks; travel/housing stipend may be available for eligible interns residing >50 miles away.