Ph.D. in a scientific discipline with 3+ years of relevant experience or M.S. with 10+ years of relevant experience.
Proven experience in protein directed evolution and library design.
Hands-on expertise in protein engineering and molecular biology techniques.
Familiarity with computational methods for protein engineering.
Experience in developing screening and selection methods for protein libraries.
Strong scientific judgment and troubleshooting skills with attention to detail.
Excellent written and verbal communication skills.
Responsibilities
Conduct directed evolution campaigns to enhance gene editing proteins.
Create protein libraries and variants through molecular cloning and mutagenesis.
Design gene editing proteins using machine learning and structural analysis.
Execute iterative cycles linking computational predictions with experimental outcomes.
Perform biochemical and cell-based assays to assess gene editing performance.
Analyze datasets to uncover sequence-function relationships for design prioritization.
Collaborate with computational scientists to refine predictive models based on experimental data.
Benefits
Collaborative work environment with interdisciplinary teams.
Opportunities for publication and contribution to intellectual property.
Access to cutting-edge technology and methodologies in gene editing.
Potential for impactful contributions to therapeutic development.
Support for professional growth and development in a dynamic field.
Full Job Description
The Role
We are seeking a scientist to engineer and optimize gene editing proteins by combining machine learning and protein language models with hands-on laboratory research. This individual will design protein variants, build and test them, and use experimental results to guide subsequent engineering cycles. Working closely with computational and translational scientists, this role will advance gene editing systems with improved activity, specificity, and properties relevant to therapeutic development.
Here's What You'll Do
Carry out directed evolution campaigns to improve activity and specificity of gene editing proteins.
Generate protein libraries and variants through molecular cloning, mutagenesis, and related engineering approaches.
Design and engineer gene editing proteins using sequence and structural analysis, machine learning, and protein models.
Develop and execute iterative cycles that connect computational predictions with experimental results.
Develop and perform biochemical and cell-based assays to evaluate gene editing efficiency, specificity, and performance.
Analyze experimental datasets to identify sequence-function relationships and prioritize subsequent designs.
Collaborate with computational scientists to adapt and evaluate predictive models using experimental data.
Partner with translational teams to assess engineered systems in relevant biological contexts.
Communicate findings and recommendations clearly, maintain rigorous documentation, and contribute to technical reports, intellectual property, and publications.
Requirements
Ph.D. in scientific discipline and a at least 3 years of relevant experience OR M.S with at least 10 years of relevant experience.
Experience in protein directed evolution, including library design, use of oligo pools, and development of selection strategies.
Hands-on experience in protein engineering and molecular biology, including construct design, cloning, mutagenesis, and protein variant generation.
Familiar with computational approaches used for protein engineering.
Experience in developing and establishing screening and selection methods. Including assessing library quality and performing QC to optimize selection strategies.
Strong scientific judgment, troubleshooting skills, attention to detail, and commitment to reproducible research.
Clear written and verbal communication skills.
Preferred Qualifications
Experience engineering or characterizing gene editing systems, such as CRISPR-associated nucleases, base editors, or large serine recombinases.
Experience with use of FACS for cell sorting and selection.
Experience with high-throughput screening or deep mutational scanning.
Experience optimizing protein properties relevant to therapeutic use, including potency, stability, expression, and delivery compatibility.
Experience with use of NGS to support protein engineering.
Experience with protein expression, purification, and biochemical characterization.
Practical experience applying machine learning and protein language models to protein design, variant prioritization, or sequence-function prediction.
Familiarity with off-target assessment and engineering approaches to improve editing specificity.
The budgeted range for this position is $125,000 - $165,000. This range is a good faith estimate of the expected salary range for this position, based on a wide range of factors including qualifications, experience and training, operational and business needs and other considerations permitted by law.
About ElevateBio
ElevateBio is a biotechnology company that develops and commercializes gene and cell therapies. The company's platform includes a portfolio of companies that specialize in different areas of gene and cell therapy development, including manufacturing, clinical development, and commercialization. ElevateBio's goal is to accelerate the development of gene and cell therapies to address unmet medical needs. The company was founded in 2019 by David Hallal and Nina Kjellson, two experienced biotech executives.
