Company Overview: Terray Therapeutics is a venture-backed biotechnology company led by pioneers and long-time leaders in artificial intelligence, synthetic chemistry, automation, and nanotechnology. We’re generating chemical data purpose-built to propel drug discovery into the information age — and we’re doing it on a larger scale and faster than has ever before been possible.
Our closed loop system generates precise chemical datasets at unrivaled scale that work seamlessly with AI to systematically map biochemical interactions between small molecules and causes of disease. Iterative cycles of virtual molecular design and experimentation power AI and machine learning models, which in turn guide the next cycle of design. With a chemistry engine that measures billions of interactions daily and becomes increasingly precise with every cycle, we can answer an unprecedented array of questions — deriving insights that enable us to predictably create drugs for patients in need.
Position Summary: Terray is currently seeking a motivated, creative, and experienced cheminformatics scientist. As an integral member of our Computational and Data Sciences (CDS) team, the candidate will be responsible for developing and applying cheminformatics tools for library design, hit analysis and expansion, and molecular design.
The core responsibilities of this position are:
- Work with chemists to design diverse and focused screening libraries with up to hundreds of millions of molecules using available building blocks and enabled reactions
- Develop fast, reaction-based enumeration methods for enumerating real and virtual combinatorial libraries
- Manage a relational database and Snowflake data warehouse with information about building blocks and enumerated combinatorial molecules
- Work with building block vendors to characterize their catalogs and help with purchases to expand the Terray chemical space
- Implement algorithms for molecular generation and synthesizability
- Develop tools for analyzing binding data from our proprietary screening platform and leverage them to identify hits for follow-up synthesis
- Develop scalable, in-house tools for clustering, similarity, feature generation, etc.
- Work with machine learning scientists to develop and test 2D molecular features
Experience and Qualifications: Part of Terray’s success is nurtured by a hands-on work environment where everyone is accountable, vested in a vision of excellence, and actively taking part in the success of the business. Terray supports a positive work environment where employees can feel engaged, recognized and empowered to be creative.
- BS/MS/PhD in Computer Science, Applied Math, Computational Chemistry, or related quantitative field
- Highly proficient in Python and the PyData stack (numpy, pandas, scipy, scikit-learn, etc.)
- Proficiency in Linux environment, experience with database languages, and experience with version control practices and tools
- Familiar with AWS cloud resources
- Experience with RDKit or related cheminformatics software (Daylight, OEChem, OpenBabel, Vortex, Spotfire, etc.)
- Experience with at least one computational chemistry simulation suite (Schrodinger, MOE, etc.)