Summer Internship: Clinical Pharmacology AI ML Intern

BeiGene

4d•Hybrid

About The Position

BeOne continues to grow at a rapid pace with challenging and exciting opportunities for experienced professionals. When considering candidates, we look for scientific and business professionals who are highly motivated, collaborative, and most importantly, share our passionate interest in fighting cancer. Internship program dates: June 8 - August 21, 2026 Education Required: Currently enrolled in an MS or PhD program General Description: Open to pharmaceutical scientists or AI engineers eager to apply advanced analytics to drive innovation in drug development This internship program is to provide intern exposure to the field of clinical pharmacology and various modeling and simulation tools used to support drug development, including PBPK, scientific machine learning pharmacodynamic models and autoencoder generative machine learning model Under the supervision of the manager, the intern will have an opportunity to apply AI/Machine Learning or Large Language Model to work with large clinical datasets, and to participate in developing a predictive model. Develop proficiency in the use of software tools for the development of PBPK, PK/PD models and the R programming language for data management Attend Department meetings to gain exposure to drug development process Flexible start date Remote or on-site options available

Requirements

Currently enrolled in an MS or PhD program
Open to pharmaceutical scientists or AI engineers eager to apply advanced analytics to drive innovation in drug development
Familiar with R or Python and experience in data analysis using AI/ Machine Learning and Large Language Model is a plus.

Responsibilities

Literature review and data management: Review and capture literature source for used in the modeling; transform raw clinical datasets into a format that makes it valuable for downstream analysis.
Model development, verification and validation: learn how to develop semi-mechanistic models to support drug development; learn how to apply AI/large Language Model to support the analysis and reporting applicable in accelerated drug development.