Post Doctoral RA – Synthetic Biology and Biosensor Design

Overview

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.

Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.

The Earth and Biological Sciences Directorate (EBSD) leads critical research in four areas:
Atmospheric, Climate & Earth Sciences, Biological Sciences, Environmental Molecular Sciences, and Global Change. Our vision is to develop a predictive understanding of biological and Earth systems in transition. We aim to understand energy and material flows within the integrated Earth system; to understand, predict, and control the response of biosystems to environmental and/or genomic changes; and to Model the Earth system from the subsurface to the atmosphere.

The Environmental Molecular Sciences Division is comprised of 18 interdisciplinary research teams focused on deciphering molecular-level interactions driving biological and environmental processes across temporal and spatial scales. Through computational analysis and modeling, these findings contribute to predictive understanding of how systems respond to environmental perturbations thus enabling solutions to the nation’s energy, environmental, and human health challenges. The division also manages the Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus that accelerates the research of scientists around the world by providing access to world-class expertise, instrumentation, and computational resources.

The Functional and Systems Biology Group in the Environmental Molecular Sciences Division at Pacific Northwest National Laboratory (PNNL) is seeking a motivated researcher with strong expertise in biosensors and high-throughput strain engineering to advance automated phenotyping and genome editing workflows. The overarching goal is to develop robust microbial, fungal, and algal platforms for biofuels and bioproducts through genetic and phenotypic optimization.

A central focus of this position is the design, development, and application of biosensors—both in vivo and in vitro—to detect and quantify phenotypic signatures that enable rapid, data-driven strain improvement. Experience with cell-free systems for biosensor development, characterization, and application is highly desirable.

The successful candidate will lead efforts to develop, optimize, and validate genetically encoded and/or synthetic biosensors that report on cellular states, metabolic fluxes, and target molecule production in microbial, fungal, and algal systems. This work will span in-vivo deployment in living cells and organisms, in vitro application in cultured cells, organoid-like and microfluidic platforms, and cell-free expression or metabolic systems used to prototype and tune biosensors prior to deployment.

The candidate will integrate biosensor readouts with automated cultivation and genome editing tools to enable high-throughput screening, closed-loop strain engineering, and rapid mapping of genotype–phenotype relationships.

Other key responsibilities include designing, developing, and implementing high-throughput automated workflows for the EMSL User Program. These workflows will integrate biosensor-based phenotyping with high-resolution, single-cell analyses and multi-modal techniques (e.g., transcriptomics, proteomics, metabolomics) to uncover genetic drivers of phenotypic traits, elucidate protein function, and guide iterative strain improvement.

The candidate will work within a multi-researcher, interdisciplinary team to engineer strains with enhanced traits using genome editing and synthetic biology tools, informed by biosensor and multi-omics data. They will refine biosensor designs and phenotyping strategies across cell-free, in…