Develop novel proteins with specific functionalities using state-of-the-art machine learning algorithms and computational methods.
Requirements
- Ph.D. in Computational Biology, Computer Science, Mathematics, or related discipline.
- 3+ years of experience (including PhD work) in applying deep learning methods to problems related to protein sequence-structure-function relationships.
- Demonstrated ability to deliver deep learning models to production use.
- Strong technical proficiency in coding (including ML frameworks), cloud computing, and dev ops.
- Knowledge of protein biochemistry and structural biology
- Working experience with design of multi-subunit complexes and membrane proteins
- Experience with cloud computing platforms (e.g., AWS, Google Cloud) for large-scale data processing.
Responsibilities
- Develop and apply protein modeling and design strategies to advance the company’s platform.
- Devise, train, refine, and deploy deep neural network models using public and proprietary sequence, structure, and function data.
- Collaborate closely with experimental scientists to close the model-test-learn loop.
- Drive external collaborations where necessary to augment internal capabilities.
- Create, maintain, and update documents for all aspects of the development process as well as contributing to generating intellectual property
Other
- Outstanding written and verbal communication skills, ability to work with colleagues from diverse scientific backgrounds and cultures.
- Preferably a track record of success working in a fast-paced, cross-functional, and rapidly growing biotech organization.
- Ph.D. in Computational Biology, Computer Science, Mathematics, or related discipline.
- Equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
