Computational Protein Research Associate (Contract)

Zymo Research; Tustin (CA); On-site; USD 75,000 - 85,000; Full time

Benefits offered by this job

Medical, Dental, Vision, and Life Insurance Coverages

Generous 401(K) with matching

Employee Referral Bonus

Complimentary fruit, snacks, and beverages

Complimentary catered lunches on Thursdays

Complimentary EV Charging

Cell phone stipend

Job summary

Zymo Research in Tustin, CA is looking for a passionate Computational Protein Research Associate to enhance our research team focusing on protein engineering and molecular modeling. Candidates should have a degree in computational biology or a related field and experience in machine learning applications.

This role includes working with advanced modeling tools like AlphaFold and conducting experiments in collaboration with wet-lab scientists. The estimated compensation ranges from $75,000 to $85,000, alongside competitive benefits including medical coverage and a 401(K).

Qualifications

• Bachelor’s degree or higher in relevant field required.
• Strong foundation in computational protein science or structural biology.
• Experience with machine learning or deep learning methods is essential.

Responsibilities

• Develop protein sequence–structure–function analysis platforms.
• Build predictive AI/ML models for protein design.
• Apply machine-learning approaches to analyze protein sequences.

Skills

Computational protein science

Machine learning

Python programming

Analytical skills

Communication skills

Education

Bachelor’s degree in computational biology, bioinformatics, structural biology, or related field

Tools

AlphaFold 3

Rosetta

Molecular dynamics simulations

Job description

Zymo Research is seeking a highly motivated and innovative Computational Protein Research Associate to join our multidisciplinary research team focused on protein engineering, enzyme discovery, antibody design, and AI-driven molecular modeling.

The successful candidate will work at the intersection of computational biology, machine learning, structural biology, and protein engineering. Key responsibilities will include developing scalable protein sequence–structure–function analysis platforms, building predictive AI/ML models, and identifying or designing proteins with desired biological properties. This role offers the opportunity to contribute to cutting‑edge platform technologies in enzymes, antibodies, synthetic biology, and molecular diagnostics.

Essential Duties and Responsibilities

• Apply protein language models and other machine‑learning approaches, including model fine‑tuning, to analyze protein sequences, predict molecular properties, and annotate protein functions.
• Use structural modeling and simulation tools, including AlphaFold 3, Rosetta, and molecular dynamics simulations, to investigate protein structures, conformational stability, molecular interactions, and functional mechanisms.
• Apply AI/ML methods to de novo protein design, protein optimization, enzyme engineering, antibody design, and functional prediction.
• Perform computational screening and prioritization of candidate proteins for experimental validation.
• Collaborate closely with wet‑lab scientists to design experiments, interpret results, and iteratively improve engineered proteins.
• Contribute to active‑learning‑driven Design–Build–Test–Learn cycles for protein engineering and optimization.
• Present research findings internally and externally through reports, publications, and scientific conferences.
• Contribute to intellectual property generation and platform development.

Education and Experience

• Bachelor’s degree or higher in computational biology, bioinformatics, structural biology, computer science, biophysics, protein engineering, or related field.
• Strong foundation in computational protein science or structural biology.
• Experience applying machine‑learning or deep‑learning methods to biological sequence, structure, or functional data.
• Proficiency in Python and commonly used scientific computing and machine‑learning libraries.
• Experience with protein language models, structure‑based modeling, or molecular simulation is highly desirable.
• Strong analytical, problem‑solving, and communication skills.
• Ability to work independently while contributing effectively within a multidisciplinary research environment.

Compensation, Benefits, and Perks

The estimated base compensation range for this position is $75,000-85,000 at the time of posting. Actual compensation details will be provided in writing at the time of offer, if applicable, and are based on several factors we believe fairly and accurately reflect the role, including geographic location, experience, knowledge, skills, abilities, and other job‑permitted factors.

Zymo Research also offers competitive benefits and perks including:

• Medical, Dental, Vision, and Life Insurance Coverages
• EAP Sessions
• Generous 401(K) with matching
• Employee Referral Bonus
• Complimentary fruit, snacks, and beverages
• Complimentary catered lunches on Thursdays
• Complimentary EV Charging
• Cell phone stipend

Equal Employment Opportunity Employer

Zymo Research welcomes candidates of all backgrounds. These include sex, age, color, race, religion, marital status, national origin, ancestry, sexual orientation, gender, gender identity, gender expression, physical & mental disability, medical condition, genetic information, military and veteran status, or any other protected status as defined by federal, state, or local law.

Location

Onsite – Zymo Research – 2961 Dow Ave, Tustin, CA 92780

Disclaimer

At Zymo, we take the integrity of our hiring process seriously. Please be aware of fraudulent recruitment activities that may use our name to deceive job seekers. We will never ask for payment, sensitive personal information, or financial details during the recruitment process.

All legitimate communications will come from an official Zymo or TriNet Hiring email address. If you are contacted by anyone claiming to represent us using a free email service (e.g., Gmail, Yahoo, Hotmail) or asking for payment, please treat this as fraudulent and report it immediately to [e-mail].