Company Overview:

Terray Therapeutics is a venture-backed biotechnology company leveraging our vast high-quality data to optimize the path from discovery to transformative therapeutics. Our approach delivers on the promise of computation to revolutionize drug discovery. Through our closed-loop wet lab discovery platform and data-rich AI, we overcome existing constraints on chemical data by systematically mapping the biochemical interactions of massive and diverse small molecule libraries to identify novel therapeutic compounds. Access to this quantitative data at scale allows us to intelligently navigate an infinitely extensible and highly diverse chemical space to efficiently design, discover and optimize small molecule therapeutics. Our internal development programs are focused on immunology. In addition to these programs we also work with leading pharmaceutical companies.  

Our integrated computational platform, tNova, harnesses our novel affinity binding technology, tArray, unique resynthesis capabilities, and broad biology infrastructure. tArray is the foundation of our discovery engine. It enables us to screen hundreds of millions of compounds in minutes and return quantitative data on each compound. Vast, high purity, and high diversity compound libraries are rapidly iterated using best-in-class chemistry to unlock chemical insights at the scale necessary to power AI-driven drug discovery.

Position Summary: Terray Therapeutics is seeking a motivated, creative, and experienced Computational Chemist. As an integral member of our data team, the candidate will be responsible for applying state-of-the-art computational approaches to accelerate the design of small molecules at all stages of the drug discovery pipeline. The position will report to the Head of Computational and Data Sciences.

The core responsibilities of this job will be

  1. Apply ligand-based (conformational analysis, flexible alignment, etc.) or structure-based (docking, scoring, etc.) drug design approaches at all stages of the drug discovery pipeline
  2. Develop fast, reaction-based and string-based enumeration techniques for screening libraries
  3. Work with chemists to design screening libraries from available building blocks and reactions
  4. Develop and improve hit finding criteria that is tailored to our screening platform
  5. Develop QSAR/machine learning models for understanding and predicting affinity, activity, ADME, and physiochemical properties

Experience and Qualifications:

Given the company’s size, anticipated growth and fast-paced environment, the organization requires a computational chemist who is thoughtful, high energy and can partner with the broader organization to further enhance our next generation drug discovery capabilities.

Part of Terray Therapeutics’ success is nurtured by a hands-on work environment where everyone is accountable, everyone is vested in a vision of excellence, and everyone actively takes part in the success of the business. Terray Therapeutics supports a positive work environment comprised of engaged employees who feel appreciated, recognized and free to be creative.

Qualifications include:

  • PhD in Computer Science, Applied Math, Computational Chemistry, or related quantitative field
  • Experience with at least one computational chemistry simulation suite (Schrodinger, MOE, etc.)
  • Experience with RDKit and at least one docking software (AutoDock Vina, rDock, etc.)
  • Experience with at least one quantum chemistry software package (Gaussian, Q-Chem, pyscf, etc.)
  • Experience with Linux environment and AWS cloud resources
  • Proficiency in Python and the PyData stack (numpy, pandas, scipy, dask, etc.)
  • Familiarity with scikit-learn, XGBoost, and either PyTorch or TensorFlow is a plus

She/he will exhibit the ability to work well under pressure to provide results in a short timeframe. The company is looking for a highly responsive, goal-oriented individual who will bring significant energy and drive to solve complex technical problems and help us achieve our mission to advance human health.



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