Senior Scientist – Computational Chemistry

Terray Therapeutics

Remote / Monrovia, CA, US
  • Job Type: Full-Time
  • Function: Life Sciences QA/QC
  • Industry: Life Sciences
  • Post Date: 04/03/2024
  • Website: www.terraytherapeutics.com
  • Company Address: 129 N. Hill, Suite 103, Pasadena, California , 91106, US

About Terray Therapeutics

Terray Therapeutics is a biotechnology company headquartered in Pasadena, California. Terray utilizes a novel screening and optimization platform (tArray) to develop treatments for historically intractable causes of human disease.

Job Description

Company Overview

Terray is a biotechnology company with the technology, data, and mindset to radically change the way we discover and develop small molecule therapeutics. We explore molecules and targets broadly and deeply with a sophisticated integration of ultra-high throughput experimentation, generative AI, biology, medicinal chemistry, automation, and nanotechnology. Everything the company does is grounded in an iterative approach, producing massive amounts of precise, purpose-built data mapping interactions between small molecules and causes of disease that gets increasingly valuable with each cycle of design and experimentation. The company’s platform uniquely blends experimentation and computation to improve the cost, speed, and success rate of small molecule drug discovery and development. 

Position Summary

Terray is currently seeking a motivated and creative computational chemist to join the molecular design group. As an integral member of our Computational and Data Sciences (CDS) team, the candidate will work closely with the machine learning team to evaluate and assess new models that take advantage of our in-house database of binding affinity measurements and incorporate structural modeling and physics-based approaches. The candidate will additionally engage with molecular design and medicinal chemistry teams to utilize novel computational techniques in small molecule design.

The core responsibilities of this position are:

  • Collaborate with machine learning scientists to evaluate structure-based machine learning models for predicting small molecule affinity
  • Incorporate state-of-the-art techniques such as FEP into molecular design workflows
  • Partner with molecular design scientists and medicinal chemists to design small molecules using both structure-based methods and ligand-based data from our proprietary screening platform
  • Develop a high-throughput conformational analysis pipeline to be utilized in multiple structure-based workflows

Experience and Qualifications

Given the company’s size, anticipated growth and fast-paced environment, the organization requires a scientist who is thoughtful, highly responsive, 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, vested in a vision of excellence,and  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

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

Compensation Details

$160,000 - $240,000 (annually) depending on seniority; participation in the Company's option plan; 3% 401K contribution; full benefits.