Postdoctoral Research Associate

Project Title: Engineering Optogenetic Control of Feedstock Utilization in Yarrowia lipolytica

We are seeking a highly motivated and skilled individual to join a collaboration between the Senger and Wright research groups as a Postdoctoral Research Associate. The successful candidate will play a central role in a multidisciplinary project aimed at engineering programmable CRISPRai and optogenetic control systems and developing predictive metabolic models for the oleaginous yeast Yarrowia lipolytica. This position offers a unique opportunity to conduct cutting-edge research at the intersection of synthetic biology, metabolic engineering, and systems biology with applications in sustainable biomanufacturing.

The successful candidate will contribute to the development of a strain-engineering platform that enables wavelength-specific optical regulation of feedstock catabolism and fatty acid biosynthesis. This includes building and refining a genome-scale metabolic model of Y.

lipolytica, developing optogenetic and CRISPR-based logic circuits, and using Raman spectroscopy to monitor cellular responses and validate model predictions. The work will directly inform the design of multiplexed strains capable of efficiently converting diverse feedstocks into valuable bioproducts.

Ph.D. in Synthetic Biology, Metabolic Engineering, Systems Biology, Chemical Engineering, Biological Engineering, or a related field. Ph.D. must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
Strong background in molecular biology and genetic engineering of eukaryotic microbes.
Experience with synthetic biology tools such as modular cloning, CRISPR/Cas systems, and transcriptional regulation.
Demonstrated ability to work independently and as part of a team.
Excellent written and oral communication skills.

Experience with Yarrowia lipolytica or other non-model yeasts.
Expertise in optogenetics, light-controlled gene expression systems, and photoreceptors.
Familiarity with metabolic modeling (e.g., COBRA methods), genome-scale modeling, or flux balance analysis.
Experience with Raman spectroscopy, flow cytometry, or single-cell analysis tools.
Competence in bioinformatics tools for model refinement or omics integration.

Exempt: Not eligible for overtime

Restricted

53,550-65,029

40

06/22/2025

The successful candidate will be required to have a criminal conviction check.

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance.  These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.