About the role#
This internship focuses on protein therapeutics and AI research. You will work on projects that support the discovery and development of scientific innovations. The role involves using computational methods to improve our understanding of biologics stability and developability.
What you'll do#
- Apply structural modeling, molecular dynamics, and machine learning to identify novel molecular descriptors.
- Benchmark existing machine learning methods for predicting the developability of multi-specifics.
- Build a preliminary developability prediction workflow by integrating internal data, computational descriptors, and external knowledge.
- Document and deposit all code created during the term.
- Write and update SOPs as needed.
- Present your work at the conclusion of the internship.
What you'll need#
- Enrollment in a Bachelor’s, Master’s, MBA, JD, or PhD program in Computer Science, Physics, Mathematics, Statistics, or Data Science.
- Continued full-time enrollment in the Fall semester following the internship.
- A minimum cumulative GPA of 2.8.
- Ability to commit to 10 to 12 consecutive weeks of full-time work between May and August.
- Must be at least 18 years of age.
- Independent authorization to work in the United States without company sponsorship.
Location & details#
- This position is based in Foster City, California.
- The role is hybrid and requires working on-site.
- This is a paid, full-time internship for Summer 2027.
About Gilead Sciences
Gilead Sciences is a biotechnology research company based in Foster City, California. It focuses on the development of medicines in the fields of virology and oncology. The company operates as a public entity with more than 10,000 employees. Its work includes efforts to address health inequities and remove barriers to medical care.
How to get in at Gilead Sciences
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