Platform Scientist: Protein Design & Assay Lead

Anthrogen; San Francisco (CA); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Equity 0.05–0.5%

Job summary

Anthrogen in San Francisco is seeking an experimental scientist to own research on designed proteins and assemblies. You will develop assays, analyze results, and interpret why experiments succeed or fail in cellular contexts.

You will collaborate with ML researchers to convert outcomes into design constraints for the next generation of proteins, emphasizing depth, rigor, and independent initiative.

Qualifications

• Track record of original experimental research and ability to explain personal findings.
• Deep hands-on expertise in protein biochemistry, molecular biology, cell biology, or closely related field.
• Ability to build and troubleshoot an assay and recognize misleading results.
• Ability to drive a research direction independently while documenting work for reproducibility.

Responsibilities

• Drive experimental research from the initial question through assay design, execution, analysis, and next design decision.
• Build quantitative biochemical and functional assays for designed proteins and their assemblies in relevant cellular contexts.
• Distinguish real biological activity from assay artifacts with controls and independent measurements.
• Work closely with ML researchers to translate successes and failures into design constraints for future iterations.
• Develop methods reliable across constructs, targets, and repeated experiments, and help colleagues use them.

Skills

Experimental research

Protein biochemistry

Molecular biology

Cell biology

Assay development

Data interpretation

Independent work

Written communication

Tools

Python

Lab automation

Job description

Anthrogen in San Francisco is seeking an experimental scientist to own research on designed proteins and assemblies. You will develop assays, analyze results, and interpret why experiments succeed or fail in cellular contexts.

You will collaborate with ML researchers to convert outcomes into design constraints for the next generation of proteins, emphasizing depth, rigor, and independent initiative.