Apply on Employer Site

Pacific Northwest National Laboratory · 4 hours ago

Post Doctorate RA - HTP-Strain Engineering and Phenotyping

Richland, WA

Full-time

Onsite

New Grad, Entry Level

$69K/yr - $119K/yr

Pacific Northwest National Laboratory (PNNL) is a world-class research institution focused on scientific research and innovation. They are seeking a motivated researcher to advance high-throughput strain engineering and phenotyping using genome editing tools and automated systems to develop robust platforms for biofuels and bioproducts.

Biomass EnergyEnergyGovernmentProduct ResearchSecurity

Growth Opportunities

No H1B

U.S. Citizen Only

Responsibilities

Designing, developing, and implementing high-throughput automated workflows for the EMSL User Program and DOE BER-sponsored projects

Integrate high-resolution, single-cell phenotyping with multi-modal techniques (e.g., transcriptomics, proteomics, metabolomics) to uncover genetic drivers of phenotypic traits, elucidate protein function, and guide strain improvement

Collaborate within a multi-researcher team to integrate experimental data using bioinformatics and molecular tools, refine strain engineering strategies, and contribute to scientific publications

Ensure adherence to laboratory safety and compliance standards

Qualification

Genome editing toolsStrain engineeringHigh-throughput phenotypingLab automationBioinformaticsInterpersonal communicationWritten communicationOral communication

Required

Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university

Preferred

Ph.D. in microbiology, bioengineering, microbial genetics, chemical engineering, or a related field

Demonstrated expertise in strain development, lab automation, and genetic engineering

The ideal candidate will have a Ph.D. in microbiology, synthetic biology, bioengineering, or a related field, with expertise in strain engineering, genome editing tools (e.g., CRISPR/Cas, CRISPRa/i), and high-throughput phenotyping workflows

Proficiency in using automated systems and applying multi-modal phenotyping techniques (e.g., transcriptomics, metabolomics) to link genetic drivers to phenotypic traits is highly desirable

Candidates should demonstrate experience integrating experimental data using bioinformatics tools, contributing to peer-reviewed publications, and collaborating within interdisciplinary and multi-institutional teams

The successful candidate will interact with other staff and participate in team-based collaborative research within PNNL as well as with external organizations. Therefore, strong written, oral, and interpersonal communication skills are essential for independently carrying out initial analysis of experimental data and presenting summaries to project managers and staff