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This internship focuses on clinical pharmacology and AI/ML modeling, providing experience in developing predictive models using clinical datasets.

The Executive Director of Advanced Analytics & Data Science leads BeOne's strategic vision in data analytics, AI, and machine learning, driving commercial success and innovation while managing a high-performing team and ensuring data-driven decision-making across the organization.

The intern will gain experience in data visualization, quality checks, and reporting, collaborating with cross-functional teams to improve analytics and data governance.

The Director of Clinical Development will lead and execute clinical development programs, manage teams, collaborate across functions, and ensure compliance with regulations and protocols in oncology research.

Lead statistical analyses for Real-World Data (RWD) and Evidence (RWE) studies, oversee programming deliverables, analyze large datasets, and provide statistical consultation for biostatistics projects.

The Senior Data Management Systems Admin performs admin activities for Data Management systems, supports automation with AI/ML, manages trial user administration, and collaborates on data governance implementation.

Lead global clinical program operations, oversee gCSM team development, ensure program-level strategy and execution for designated oncology/hematology programs, manage budgets/resources, drive quality and compliance (ICH/GCP), mentor staff, and serve as escalation point for program issues across international time zones.

Lead and manage clinical supply chain teams to develop demand and supply plans, ensure continuous cGMP-compliant drug supply, minimize waste and risk, manage budgets, drive CAPA and process improvements, and coordinate with internal and external stakeholders supporting clinical trials.

The Associate Director manages technology transfer for drug product development, collaborating with various stakeholders to ensure project success and maintaining manufacturing processes.

Summer internship for MS/PhD students to apply AI/ML and LLMs to clinical pharmacology datasets, perform literature review and data management, and develop/validate PBPK and PK/PD models using tools like R or Python.