π Local Job Near You
Senior Specialist, Computational Protein Design
Merck
π
South San Francisco, United States
Location
South San Francisco
Posted
June 24, 2026
Commute
Local Area
Local Opportunity Near You!
This job is in your area. Enjoy a short commute and work close to home.
Job Description
**Job Description**
We are seeking an innovative and experienced computational protein design scientist to join the Discovery Biologics Protein Engineering department. In this role, you will lead AI- and structure-guided protein design efforts, driving iterative design cycles from concept to candidate. As a functional subject matter expert, you will interface across Discovery Biologics, computational biology, and therapeutic area teams to shape and execute our AI-enabled protein design strategy.
We recognize that our team is our strength and are committed to creating an inclusive environment for all employees. Successful candidates must demonstrate inclusive behaviors in working with a group of scientists to drive our core mission.
**What you will do:**
+ Familiar with the state-of-the-art generative models (e.g., RFDiffusion, ProteinMPNN, ESM3) and apply these protein design methods within iterative designβtestβlearn cycles; benchmark approaches aga...
We are seeking an innovative and experienced computational protein design scientist to join the Discovery Biologics Protein Engineering department. In this role, you will lead AI- and structure-guided protein design efforts, driving iterative design cycles from concept to candidate. As a functional subject matter expert, you will interface across Discovery Biologics, computational biology, and therapeutic area teams to shape and execute our AI-enabled protein design strategy.
We recognize that our team is our strength and are committed to creating an inclusive environment for all employees. Successful candidates must demonstrate inclusive behaviors in working with a group of scientists to drive our core mission.
**What you will do:**
+ Familiar with the state-of-the-art generative models (e.g., RFDiffusion, ProteinMPNN, ESM3) and apply these protein design methods within iterative designβtestβlearn cycles; benchmark approaches aga...