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Post Doctoral RA – Synthetic Biology Biomining

Job in Richland, Benton County, Washington, 99354, USA
Listing for: PNNL
Full Time position
Listed on 2026-08-24
Job specializations:
  • Research/Development
    Research Scientist, Genetics / Genomics
Job Description & How to Apply Below
Position: Post Doctoral RA – Synthetic Biology for Biomining

Researcher Position in Synthetic Biology and High-Throughput Strain Engineering

The Functional and Systems Biology Group in the Environmental Molecular Sciences Division at PNNL seeks a motivated researcher with strong expertise in synthetic biology and high-throughput strain engineering to elucidate and exploit the fundamental molecular mechanisms governing rare earth element (REE) acquisition, accumulation, and sequestration in microbes. The position supports a project establishing biodesign principles for selective REE recovery from dilute, complex sources using genetically tractable non-model bacteria.

The successful candidate will lead strain engineering and synthetic biology efforts to interrogate and re-engineer these mechanisms. This includes applying modern genetic tools to identify genes that influence REE uptake, handling, and tolerance; modulating relevant metabolic pathways to understand the limits of accumulation capacity; developing genetic parts and regulatory systems that place accumulation and release under programmable control; and building and screening libraries of candidate proteins and regulatory elements to improve performance.

A closely coupled focus is the design and application of biosensors for in vivo reporting on intracellular metal dynamics, nutrient status, stress response, and efflux. The candidate will deploy compartment-localized sensors with fluorescent, colorimetric, and growth-based outputs, use cell-free expression to prototype designs, and couple sensor readouts to actuator expression for self-regulating release. Integration with automated cultivation will enable high-throughput screening, closed-loop Design-Build-Test-Learn cycles, and rapid genotype–phenotype mapping, supported by high-throughput workflows that link biosensor phenotyping with spatially resolved and multi-omics analyses.

The candidate will work within a multi-researcher, interdisciplinary, multi-institutional team; integrate datasets using bioinformatics tools; deliver validated constructs, strains, and data on project milestones; contribute to publications, technical reports, lab protocols, and adhere to laboratory safety and compliance standards.

** Position is onsite only, and located in Richland, WA.**

Qualifications

Minimum Qualifications:

  • 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 Qualifications:

  • Ph.D. in bioengineering, microbial genetics, chemical engineering, synthetic biology, microbiology, biotechnology, or a related field, with demonstrated expertise in microbial strain engineering and synthetic biology, including strain optimization and troubleshooting of engineered pathways.
  • Strong background in genome editing and gene regulation, including CRISPRi, CRISPR guide design, plasmid construction, and genomic integration, with experience genetically manipulating non-model or undomesticated microbes. This includes demonstrated ability to construct and screen large combinatorial libraries (e.g., Golden Gate assembly of multi-transcriptional-unit constructs, Gibson assembly, restriction-free cloning) and to develop plate-, growth-, flow-cytometry-, or image-based screening assays integrated with automated cultivation.
  • Experience with biosensor design and application in vivo and in vitro, including split-enzyme or split-polymerase architectures; familiarity with cell-free expression for sensor prototyping is desirable.
  • Proficiency in protein expression and analytical characterization (SDS-PAGE, Western blotting, FPLC) and in applying multi-modal phenotyping and bioinformatics/structural tools to link genetic drivers to phenotypic traits. Familiarity with metal-focused or spatially resolved analytics (ICP-MS, nanoSIMS, cryo-EM, ³¹P NMR, native MS) is advantageous.
  • Experience contributing to large, milestone-driven, multi-institutional programs (DOE, DARPA, or comparable), with timely delivery of data and reagents to collaborating teams.
  • A strong record of peer-reviewed publications, successful collaboration within interdisciplinary and multi-institutional teams, and experience supporting user or collaborative research programs are all advantageous. Strong organizational and communication skills, along with a demonstrated commitment to laboratory safety and compliance, are essential for success in this role.
  • Demonstrated expertise in strain development, lab automation and genetic engineering.
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