Research Scientist - Computational Biologist
HybridIndianapolis, Indiana, United States
Job Summary
Utilize and develop AI-driven tools like AlphaFold and Rosetta to predict and design high-resolution structures of antibodies and proteins for the therapeutic biologics pipeline. Apply generative AI and structural modeling techniques to create novel antibody modalities, proactively engineer out liabilities such as aggregation, and train ML architectures to enhance developability. Partner closely with wet-lab scientists to analyze experimental data, validate computational predictions, and rapidly iterate on designs to accelerate antibody selection. Stay current with the evolving AI landscape by evaluating new tools, maintaining thorough documentation, and communicating complex findings to cross-functional teams. This role offers a unique opportunity to grow your skills in a rapidly evolving field while contributing to tangible, real-world outcomes in animal health therapies.
Required Qualifications
- Ph.D. in Computational Biology, Bioinformatics, Structural Biology, Computer Science, or a related field
- 0-3 years of post-graduate experience applying computational methods to biological problems
- A strong foundation in structural bioinformatics and AI/ML modeling
- Proficiency in a programming language like Python
- The communication skills to work effectively in a cross-functional scientific environment
Desired Qualifications
- Experience with de novo protein design tools, such as diffusion models or physics-based approaches
- A track record of applying computational tools to solve biological problems, evidenced by publications or significant project contributions
- Familiarity with cloud computing environments (e.g., AWS, GCP) and MLOps principles
- Experience in antibody or protein engineering and a foundational understanding of immunology
- A proactive mindset with a passion for staying current with the rapidly evolving AI landscape and a motivation to test and evaluate new methodologies
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