Research Scientist, AI for Clinical Translatability

Role Description

We're looking for a Research Scientist who shares our vision for transforming healthcare. This is a unique opportunity to apply your expertise in a fast-paced, collaborative environment where you'll be instrumental in developing the tools that will redefine what is possible in drug discovery, virtual cell, and beyond. As part of our team, you'll work alongside other researchers, developers, and experts in the field to tackle some of the most challenging and impactful problems of our time.

• Building models and datasets that connect early drug discovery to the clinic, spanning drug perturbation prediction, clinical translatability, patient stratification, and digital twins.
• Designing benchmarks and evaluation methods for agentic systems in this domain, and characterizing where current LLMs underperform.
• Publishing original research and releasing open-source software.
• Collaborating with external research leaders in digital biology.
• Partnering with research and engineering teams across NVIDIA to move research into products and services.

Qualifications

• Bs/Ms or PhD in a quantitative field: computational biology, computer science, computational chemistry, physics, mathematics, or equivalent experience.
• Publication record in digital biology, ideally with clinical applications.
• 5 plus years of experience building and training machine learning models at scale, along with the compute infrastructure that supports them.
• Proficiency with modern ML frameworks such as PyTorch or JAX.
• Fluency with the statistical foundations this work rests on (causal inference, experimental design, or clinical biostatistics).
• Ability to learn from and teach others to keep up to speed on the latest developments and tools in the field.
• Ability to work together in a tight-knit team environment.

Requirements

• Track record of state-of-the-art methods development in the clinical domain.
• Experience with clinical trial data, electronic health records, or regulatory science.
• Rigor in evaluation: temporal validation, benchmark design, assessing data leakage and easy inference, characterizing distribution shift.
• Background in open-source development.

Benefits

• Competitive salaries.
• Generous benefits package.
• Equity eligibility.