Computational Protein Research Associate (Contract) at Zymo Research Corporation

Tustin, California, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Sep, 26

Salary

85000.0

Posted On

27 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computational Biology, Machine Learning, Structural Biology, Protein Engineering, Python, Deep Learning, AlphaFold 3, Rosetta, Molecular Dynamics Simulations, Bioinformatics, De Novo Protein Design, Enzyme Engineering, Antibody Design, Protein Language Models, Scientific Computing, Data Analysis

Industry

Biotechnology Research

Description

Job Summary: 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. Join us in making a meaningful impact! 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. About Us: Since its inception in 1994, Zymo Research has been proudly serving the scientific community by providing innovative, reliable, and high-quality research tools and products. Whether it's DNA, RNA, epigenetics, microbiomics, protein, or yeast-based research, our philosophy remains the same: To provide the highest quality products in the industry while ensuring they are both simple to use and reliable in their performance. Recognized as a Top Workplace by the Orange County Register in 2021, 2022, and named a Top Workplace USA in 2023, Zymo Research continues to be a vibrant community where employees thrive, feel connected, and are inspired by their work. If you are passionate about contributing to scientific advancement and want to be part of an exceptional team in a dynamic, growing company, we'd love to hear from you! 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 is based on several factors we believe fairly and accurately impact compensation, 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 * Vacation Time plus Company Holidays * Paid Sick Leave * 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 jobs@zymoresearch.com [jobs@zymoresearch.com]

Responsibilities

Develop scalable protein analysis platforms and predictive AI/ML models to design proteins with specific biological properties. Collaborate with wet-lab scientists to iteratively improve engineered proteins through Design-Build-Test-Learn cycles.