Post Doctoral Scholar - Siegel Lab

Position overview. Salary range:

$71,491-$85,736

The Siegel Lab is seeking a Postdoctoral Scholar to lead the discovery, engineering, and characterization of enzymes for next-generation metabolic health technologies. The project combines rational protein design, AI-guided protein engineering, directed evolution, genomic mining, and high-throughput screening to discover and optimize enzyme variants.

The successful candidate will design and execute enzyme engineering campaigns, including library design, protein expression, purification, biochemical characterization, and enzyme kinetic analysis. This position provides the opportunity to translate engineered enzymes into real-world applications through collaboration with an industry partner.

• Enzyme Discovery and Library Development:
  Develop enzyme discovery pipelines integrating rational design, AI-guided protein engineering, genomic mining, and directed evolution. Design and generate enzyme variant libraries for experimental evaluation.
• High-Throughput Screening:
  Develop and optimize plate based high-throughput screening assays to evaluate enzyme activity, specificity and stability under application relevant conditions.
• Protein Engineering:
  Lead iterative enzyme engineering campaigns to improve catalytic efficiency, substrate specificity, stability, and overall performance.
• Protein Production and Characterization:
  Express, purify and characterize lead enzyme variants.
• Data Analysis and
  
  Collaboration:
  
  Analyze experimental data, document findings, and work closely with an industry partner to guide iterative enzyme optimization and technology development.
• Research Leadership:
  Mentor researchers, contribute to manuscripts and grant proposals. Support a collaborative laboratory environment.

• PhD in Biochemistry, Protein Engineering, Molecular Biology, Synthetic Biology, Chemical Biology, Biomedical Engineering, or a related field.
• Demonstrated experience in protein expression, purification, biochemical characterization, and enzyme engineering.
• Experience with high-throughput cloning, library generation, directed evolution, or enzyme screening platforms.
• Familiarity with computational approaches for protein engineering, sequence analysis, or structural biology.
• Experience with AI-based structure prediction and design tools (Alpha Fold, Chai, Boltz, RF diffusion, ProteinMPNN) and data science workflows for directed evolution.
• Excellent written and verbal communication skills, with the ability to manage multiple research projects and work effective in a collaborative environment.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.

• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer.
• UC Sexual Violence and Sexual Harassment Policy
• UC Anti-Discrimination Policy for Employees, Students and Third Parties
• APM - 035:
  Affirmative Action and Nondiscrimination in Employment

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The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.

Under Federal law, the University of California may employ only individuals who are legally able to work in the United States as established by providing documents as specified in the Immigration Reform and Control Act of 1986. Certain UC Davis positions funded by federal contracts or sub-contracts require the selected candidate to pass an E-Verify check.

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