Gilead

Overview

This internship pairs hands-on application of AI/machine learning to large-scale clinical biomarker datasets with broad exposure to how biomarker science informs oncology drug development.

About Gilead

At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe.

Requirements & Eligibility

• Must be at least 18 years of age at the start of the internship.
• Must be enrolled full-time in a Bachelor’s, Master’s, MBA, JD or PhD program at a nationally accredited U.S. college or university.
• Must have a minimum overall cumulative GPA of 2.8 at the time of application and hire.
• Must be independently authorized to work in the United States now and in the future.
• Must be able to commit to a full-time internship lasting 10–12 consecutive weeks between May and August.
• Must be willing and able to work at the designated site for the duration of the internship.

Key Responsibilities

• Analyze multi-modal data from translational biomarker projects in oncology.
• Apply machine learning and AI approaches to identify multi-omic signatures associated with treatment response and resistance.
• Build reproducible analysis pipelines, validate model performance across independent patient cohorts, and interpret which biological features drive the predictions.
• Contribute to biomarker research in collaboration with cross-functional teams.
• Participate in biomarker strategy and clinical study discussions.
• Develop data visualizations and communicate scientific findings.
• Present project results to the biomarker and oncology research community.
• Showcase your work with a final presentation (PPT) near the conclusion of your internship