Associate Scientist - Microbial Fermentation and Bioprocessing

 Position Overview 

AV is seeking a Computational Scientist specializing in Microbial Metabolic Modeling and Simulation to work with the AFRL Biological Materials and Processing Research Team to spearhead the in silico design, evaluation, and optimization of microbial hosts for advanced bioproduction and material synthesis. This role will develop predictive genome-scale metabolic models (GEMs), simulate metabolic fluxes, and identify genetic intervention strategies to maximize yield, titer, and productivity of target molecules. 

The candidate will collaborate deeply with the Wet-Lab Protein Engineering and Fermentation Teams. The core mission of this role is to generate predictive metabolic designs that guide strain engineering efforts and to use experimental results to continually refine and train predictive models. Additionally, this role will support the scaling of metabolic predictions to guide pilot-scale commercial fermentation applications. 

  Key Responsibilities 

• Translate In Silico Designs to the Bench: Serve as the primary bridge between dry-lab and wet-lab operations; take candidate metabolic pathways, knock-out strategies, and over-expression targets generated via computational modeling and successfully translate them into actionable engineering strategies for the wet-lab team. 

• Metabolic Network Reconstruction & Simulation: Generate, curate, and refine genome-scale metabolic models (GEMs) using advanced systems biology and constraint-based modeling techniques. 

• High-Throughput Simulation & Selection: Develop and execute robust, automated high-throughput computational workflows (such as Flux Balance Analysis [FBA], MOMA, or regulatory flux modeling) to screen thousands of genetic perturbation strategies, successfully isolating rare "hit" strain designs from background metabolic noise. 

• Data Integration & Loop Closure: Analyze multi-omics and fermentation data (transcriptomics, metabolomics, fluxomics) to identify sequence-activity and flux-yield relationships. You will feed this high-quality experimental data back into the computational models to validate predictive capabilities, troubleshoot failures, and guide the design of the next, smarter round of strain optimization. 

• Model & Process Optimization: Continually refine modeling constraints (pH, maintenance energy, substrate uptake rates, toxicity parameters) to ensure the simulation environment accurately reflects industrial bioprocess and fermentation conditions. Test predictive metabolic models against candidate strain performance at pilot-scale levels. 

Required Qualifications 

• Education: Ph.D. in Bioengineering, Chemical Engineering, Computational Biology, Bioinformatics, Biochemistry, Systems Biology, or a related field. (Candidates with an M.S. and 2+ years of experience will be considered). 

• Metabolic Engineering & Modeling: Design, optimize, and characterize microbial metabolic networks and predict metabolic flux using state-of-the-art computational biology and systems-level modeling techniques. Collaborate cross-functionally to translate engineered computational models into robust, scalable biological solutions for real-world applications. Experience with Corynebacterium, Escherichia, and/or Saccharomyces are strongly preferred. 

• Technical Expertise: Proficiency in constraint-based metabolic modeling (e.g., COBRA toolbox in Python/MATLAB) and experience modeling standard industrial hosts (E. coli, yeast) and/or non-conventional microbial platforms. 

• Citizenship: U.S. Citizenship is required d