Scientist, Drug Discovery Data for AI/ML
About the role
D. E. Shaw Research is seeking Ph.D.-level drug discovery scientists to join our New York–based ML Data team. This is a unique opportunity to closely collaborate with our machine learning team to help shape and implement the company’s drug discovery data strategy. Successful hires will design, identify, curate, and analyze scientific datasets (primarily chemical and biological) and support the team’s efforts in drug discovery and development in a dynamic, interdisciplinary environment.
Requirements
- Ph.D. in medicinal chemistry, pharmacology, biology, or related fields
- Hands-on experience in an industry laboratory setting
- Familiarity with assays and techniques relevant to drug discovery
- At least five years of experience in pharmaceutical or biotech companies, especially with drug discovery projects
Preferred qualifications
- Experience with Linux environments and Python
About the company
DESRES, based in New York City, develops and uses advanced computational technologies to understand the behavior of biologically and pharmaceutically significant molecules at an atomic level of detail, and to design precisely targeted, highly selective drugs for the treatment of various diseases. Among its core technologies is Anton, a proprietary special-purpose supercomputer that DESRES designed and constructed to vastly accelerate the process of molecular dynamics simulation. DESRES uses Anton machines and high-speed commodity hardware, together with machine learning methods and other computational techniques, in both internal and collaborative drug discovery programs.
Benefits
- Variable compensation in the form of sign-on and year-end bonuses
- Generous benefits, including relocation and immigration assistance
Pay
The expected annual base salary for this position is $250,000–$400,000. The applicable annual base salary paid to a successful applicant will be determined based on multiple factors, including the nature and extent of prior experience and educational background.
Schedule
We follow a hybrid work schedule, in which employees work from the office on Tuesday through Thursday and have the option of working from home on Monday and Friday.