Postdoctoral Research Associate in Protein Engineering Applied to Synthetic Biology

What You Will Do

The B-IOME group within the Bioscience Division at Los Alamos National Laboratory (LANL) leads diverse research projects in microbial and community engineering for applications across biomanufacturing, biomining, environmental remediation, and human health.

As a Postdoctoral Research Associate in our group, you will collaborate with a multidisciplinary team to develop and apply cutting-edge tools for computational protein design and high-throughput screening. Your primary focus will be generating robust, high-quality experimental datasets to power machine learning models and accelerate the Design-Build-Test-Learn (DBTL) cycle.

Specifically, you will:

• Design and engineer proteins with tailored catalytic efficiency, enhanced thermal/chemical stability, or targeted ligand and metal-binding selectivities.
• Express and characterize engineered proteins in non-model microbial hosts to evaluate their functional performance in biological systems.
• Work collaboratively with computational biologists, molecular biologists, and strain engineers to advance national security and bioeconomy missions.

• Protein Engineering & Biochemistry:
  In-depth knowledge of protein biochemistry, including recombinant expression, purification, structural biophysics, and biochemical characterization.
• Enzymology & Structure-Function Relationships:
  Demonstrated understanding of enzyme kinetics, ligand/metal-binding mechanisms, protein stability determinants, and sequence-structure-function relationships.
• Tool Deployment & Experimental Design:
  Hands-on experience developing or applying computational protein design tools and/or high-throughput assay frameworks (e.g., cell-free systems, biosensors, or display technologies) to generate structured datasets.
• Communication &
  
  Collaboration:
  
  A strong record of scientific productivity (e.g., peer-reviewed publications, conference talks) and the ability to work effectively in an interdisciplinary team environment.

Training/

Certifications:

N/A

Education/

Experience:

Ph.D. in Biological Sciences, Bioengineering, Structural Biology, Synthetic Biology, Biochemistry, Biophysics, or a closely related discipline, awarded within the last 5 years (or completed prior to start date).

Two or more qualifications as described below is highly recommended.

• Computational Protein Design & AI/ML:
  Experience with computational protein design suites (e.g., Rosetta, ProteinMPNN, RF diffusion), molecular dynamics (MD) simulations, and the application or development of AI/deep learning tools (e.g., protein language models, Alpha Fold) for structure prediction and protein engineering.
• Library Generation & High-Throughput Screening:
  Hands-on experience constructing combinatorial protein or strain libraries and deploying high-throughput screening technologies (e.g., yeast or bacterial display, FACS, or microfluidics/droplet-based assays).
• Genotype-Phenotype Mapping & Data Science:
  Demonstrated proficiency in quantitative genotype-to-phenotype mapping, high-throughput sequence-activity analysis, and preparing structured experimental datasets for training machine learning models.
• Biosensor Engineering & Directed Evolution:
  Background in engineering allosteric or chimeric biosensors (e.g., transcription-factor- or fluorescent-protein-based) for high-throughput enzyme evolution, strain screening, or environmental monitoring.
• Publication Track Record:
  Proven scientific productivity as evidenced by at least two first-authored research articles in peer-reviewed journals, along with significant contributions to a review article or a book chapter.

The work location for this position is onsite and located in Los Alamos, NM. All work…