Postdoc: AI-Driven Protein Engineering for Bioremediation

Los Alamos National Laboratory; Los Alamos (NM); On-site; USD 65,000 - 75,000; Full time

Benefits offered by this job

Medical insurance

Dental & vision insurance

Life and disability insurance

Parental leave

401(k) with company match

Tuition assistance

Flexible schedule

Onsite gym

Job summary

Los Alamos National Laboratory (LANL) Bioscience Division, Genomics and Bioanalytics (B-GEN) seeks a highly motivated postdoctoral researcher to apply artificial intelligence and machine learning to engineer proteins for environmental bioremediation applications. This interdisciplinary role blends computational modeling with experimental protein engineering and biochemistry.

Ideal candidates have training in protein modeling (AlphaFold, Rosetta) and hands-on molecular biology and cell culturing,

Qualifications

• Ph.D. in a relevant STEM field completed within the last five years or expected by start date
• Preferred training in protein modeling including AlphaFold and Rosetta
• Hands-on laboratory experience with cloning, protein expression, purification and cell culturing
• Strong peer-reviewed publication record commensurate with career stage
• Excellent written and oral communication skills; ability to obtain a DOE Q clearance (U.S. citizenship)

Responsibilities

• Perform protein structural modeling and rational design to improve enzymatic activity
• Compute analysis of protein structures and dynamics to identify beneficial mutations
• Contribute to experimental validation including cloning, expression, purification, and characterization
• Communicate results effectively in written, graphical, and oral formats

Skills

Protein modeling

Molecular biology

Cell culture

Scientific writing

Education

Ph.D. in a relevant STEM field

Tools

AlphaFold

Rosetta

Job description

Los Alamos National Laboratory (LANL) Bioscience Division, Genomics and Bioanalytics (B-GEN) seeks a highly motivated postdoctoral researcher to apply artificial intelligence and machine learning to engineer proteins for environmental bioremediation applications. This interdisciplinary role blends computational modeling with experimental protein engineering and biochemistry.

Ideal candidates have training in protein modeling (AlphaFold, Rosetta) and hands-on molecular biology and cell culturing,