Protein Design Scientist: Directed Evolution

Bazeta; Cambridge (MA); On-site; USD 110,000 - 170,000; Full time

Job summary

Dayhoff Labs in Cambridge, MA, is seeking a Research Scientist in Protein Design & Engineering. You will engineer proteins for useful chemistry, merging enzyme discovery, directed evolution, and experimental characterization.

You will own the experimental cycle, selecting starting points, building libraries, and devising screens to improve function and stability. You will collaborate with our computational and ML teams, testing designs at the bench and guiding successive rounds based on results.

Qualifications

• Proven track record in protein engineering campaigns using directed evolution or rational design.
• Hands-on molecular biology, including cloning, library construction and mutagenesis.
• Experience developing and troubleshooting enzyme assays and screening workflows with proper controls.

Responsibilities

• Design and run protein engineering campaigns from enzyme selection to screening and characterization of improved variants.
• Build and express variant libraries using site-directed, random, and combinatorial mutagenesis.
• Develop assays and high-throughput screens to reliably measure target properties.
• Express, purify, and characterize proteins, measuring kinetics, substrate scope, selectivity, and stability.
• Collaborate with computational scientists to test designs and iterate rounds of design-build-test.
• Develop enzymatic reactions and cascades, optimizing conditions and cofactors for productivity.

Skills

Protein engineering

Directed evolution

Molecular biology

Cloning

Library construction

Mutagenesis

Enzyme assays

High-throughput screening

Kinetics

Structure–function

Tools

Liquid handling robots

High-throughput screening instrumentation

Chromatography

Job description

Dayhoff Labs in Cambridge, MA, is seeking a Research Scientist in Protein Design & Engineering. You will engineer proteins for useful chemistry, merging enzyme discovery, directed evolution, and experimental characterization.

You will own the experimental cycle, selecting starting points, building libraries, and devising screens to improve function and stability. You will collaborate with our computational and ML teams, testing designs at the bench and guiding successive rounds based on results.