Senior Investigator, Free Energy Methods

Location: Roivant Sciences, Inc., 151 West 42nd Street, 15th Floor, New York, NY 10036

At Roivant, we are passionate about discovering and developing new drugs to impact patients’ lives. Since its inception in 2014, Roivant has launched over 20 portfolio companies (Vants), overseen 5 successful IPOs, established a $3B partnership with a global pharma, built a pipeline of over 40 assets across various modalities and therapeutic areas, and delivered 8 successful phase 3 readouts.

Roivant is currently building new capabilities in drug discovery and expanding its existing development engine to become the world’s leading tech-enabled pharmaceutical company. Roivant’s drug discovery capabilities are driven by our computational discovery platform, which combines preeminent physics-based tools with deep expertise in machine learning to generate unprecedented predictive power that can tackle previously intractable discovery challenges. The tight integration of this computational platform with our experimental capabilities enables the rapid design and optimization of new drugs to address a wide range of targets for diseases with high unmet need.

We believe that the future of drug discovery lies in integrating predictive sciences, biology, and medicinal chemistry to accelerate the path to new medicines. This role is an opportunity to be an architect of this paradigm shift and generate transformative benefit for patients.

Position Summary: 

Roivant Discovery is looking for an experienced computational chemist to join our computational platform team. Working closely with other platform team members, the candidate will develop and implement molecular simulation and free energy methods to enable computation-driven drug discovery 


  • Develop, implement, and evaluate models and methods in molecular simulations and free energy calculations, including but not limited to 
    • Develop and implement new free energy methods to improve the precision and accuracy of binding free energy predictions 
    • Develop and implement new interaction models in simulation software to improve predictive accuracy in binding free energy calculations 
    • Develop new protocols to expand the domain of applicability of free energy methods, e.g., to predict the relative stability of protein-protein complexes induced by molecular glues 
    • Develop end-to-end workflows of robust free energy calculations with automatic quality assurance 
  • Collaborate with platform teams to deploy the above methods in target evaluation and drug discovery projects to enable or substantially accelerate such efforts 
  • Work with experimental groups to validate and benchmark the computational models in drug discovery projects, and communicate the benchmark results and project impact across the company 

 Required Qualifications:  

  • Highly motivated to develop computational methods for discovering better medicines 
  • M.S. or Ph.D. in computational physics/chemistry, physical chemistry/chemical physics, applied mathematics, or related fields 
  • Extensive experience in molecular dynamics simulations and free energy calculations 
  • Extensive programming experience (C/C++ and Python preferred) 
  • Excellent communication skills and strong team player 

 Additional Desirable Qualifications:  

  • Experience working with a diverse team on an ambitious project 
  • Experience in deep learning and numerical optimization