NVIDIA is seeking to invent the future of foundation models for life sciences by applying modern AI techniques to drug discovery, genomics, proteomics, molecular dynamics, docking, and protein folding
Requirements
- Deep understanding of modern AI techniques: deep learning for sequences, diffusion models, LLMs, unsupervised learning
- Hands-on practical know-how of how to design, train, and evaluate large neural networks
- Excellent software engineering and design instincts in Python, C++, or similar
- Outstanding expertise in biochemistry, drug discovery, molecular biology, chemical engineering, or related fields
- 4+ years in deep learning, bioinformatics, chemical engineering, structural biology, or related fields
Responsibilities
- Designing and training large-scale machine learning models at the intersection of genomics, proteomics, and chemistry
- Experimental design for probing the capabilities and limitations of the foundation models that are developed
- Working closely with hardware and software teams to improve NVIDIA’s platforms for large-scale foundation model applications
- Engaging with the broader research community via publications, presentations, and research collaborations
- Mentoring other team members, leading research initiatives, and helping to craft strategic roadmaps
Other
- PhD (or equivalent experience) in Computer Science or Computational Biology
- Track record of excellence in engineering and research
- Ability to work in a diverse environment
- Must be eligible to work in the country without sponsorship
- Travel may be required
