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.
Roivant Discovery is looking for a research scientist in computational biophysics (or in the related field of computational structural biology) to join our computational platform team. Working closely with other platform team members, the candidate will develop and implement new computational methods that incorporate experimental data into molecular dynamics simulations to enable computation-driven drug discovery. Competitive pay, equity, strong perks, and a fun working environment, along with the opportunity to do cutting edge science to design better medicines, are all good reasons to join us!
- Develop and implement computational models that predict observables in biophysical experiments, such as nuclear magnetic resonance (NMR), hydrogen-deuterium exchange (HDX), small angle X-ray scattering (SAXS), and cryoEM, from molecular simulations
- Develop and implement methods that incorporate the biophysical data into molecular dynamics simulations so as to turn the macroscopic data into accurate atomistic structural models
- Collaborate with experimental biophysicists and biochemists to design and analyze experiments to validate computational predictions
- Collaborate with target review and drug discovery teams to model therapeutic targets to provide actionable structural and mechanistic insight
- Work with force field and simulation teams to develop models and methods to improve the accuracy of simulations
- 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
- Strong record of past research accomplishments
- Extensive past experience in molecular dynamics simulations of proteins
- Extensive experience working with biophysics experimental data, such as NMR, HDX, SAXS, or cryoEM.
- Extensive programming experience (C/C++ and Python preferred)
- Excellent communication skills and strong team player
Additional Desirable Qualifications:
- Hands-on experience with biophysical experimental techniques, or extensive experience in deep collaboration with experimental biophysicists
- Experience in structural bioinformatics
- Experience working with a diverse team on an ambitious project
Roivant Sciences provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.