Grad Co-op - Protein Design for Target Discovery

What You Will Do

During this program, you will conduct state of the art research in protein design for target discovery. Responsibilities include:

• Identify and catalog genetic variants that result in gain or loss of post-translational modifications (PTMs) on therapeutically relevant cell surface proteins.
• Apply computational and AI-based approaches to model the structural impact of PTM gain/loss on protein epitopes and therapeutic target accessibility.
• Design and optimize binders against disease-relevant epitopes exposed by loss of PTM.
• Apply laboratory binder discovery and characterization workflows to validate lead binders.
• Design and execute laboratory experiments to characterize binder specificity, target engagement, and functional activity.
• Collaborate with computational and experimental scientists to communicate research findings.

Basic Qualifications

• 18 years or older
• Graduated with a bachelors degree from an accredited college or university
• Currently enrolled in an MBA program for an MBA internship OR a Masters program for a Masters internship OR a PharmD program for a PharmD internship OR Ph.D. for a PhD internship from an accredited college or university and completion of the first year of MBA OR Masters OR Pharm D OR Ph.D. program before the internship starts
• Enrolled in an accredited college or university following the potential internship or co-op assignment
• Must not be employed at the time the internship starts
• Student must be located in the United States for the duration of the co-op

Preferred Qualifications

• Currently pursuing a PhD in Computational Biology, Bioengineering, Biochemistry, Computer Science, or a related field.
• Experience with programming in Python and/or R.
• Strong analytical, problem-solving, and communication skills.
• Experience with protein engineering, structural biology, computational protein design, or antibody discovery.
• Familiarity with AI/ML approaches for protein modeling and binder design.
• Experience with molecular dynamics simulations or protein structure prediction tools.
• Experience in conducting biochemical experiments in a research laboratory.
• Prior research experience in computational and/or experimental biological sciences.