At Atomic AI, the business problem is to pioneer new frontiers in drug discovery by developing artificial intelligence to treat previously undruggable diseases by targeting RNA.
Requirements
- Foundational knowledge of machine learning and underlying mathematical concepts.
- Proficiency in Python and deep learning frameworks (e.g., JAX, PyTorch).
- Publications at major machine learning conferences or in major scientific journal
- Research experience related to structural biology, molecular design, and drug discovery.
- Foundational knowledge of physics, chemistry, and molecular biology.
- Demonstrated ability to develop performant code.
Responsibilities
- Design and develop novel machine learning models for RNA structure prediction and drug targeting.
- Evaluate and advance the state of the art of our structure prediction platform.
- Collaborate with our wetlab team on the targeted acquisition of experimental data to improve our machine learning models.
- Develop high-quality code in a team setting.
- Analyze, interpret, and organize results and present progress to colleagues in regular research meetings.
- Work within a collaborative, high-caliber, interdisciplinary team and proactively shape the scientific and strategic vision of the company.
Other
- Ph.D., M.Sc., or M.Eng. in Computer Science, Physics, Applied Mathematics, Materials Science, Computational Biology, or related field.
- 4+ years of experience developing machine learning methods for scientific applications.
- Excellent presentation and writing skills, able to clearly communicate technical information to colleagues.
- Ability to work in a collaborative team environment
- Commitment to equal employment opportunity regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.
