NVIDIA

Life Sciences

SeniorAppliedResearchScientist

$168–305k Santa Clara, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Applied Research Scientist at NVIDIA. Skills: large-scale foundation models, deep learning, AI techniques, genomics, proteomics, chemistry. 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”

Industry & Context.

Life Sciences
Problems you'll solve

Deep understanding of modern AI techniques; Hands-on practical know-how of how to design, train, and evaluate large neural networks

What They're Looking For.

Must Have

PhD (or equivalent experience) in Computer Science or Computational Biology, 2+ years in deep learning, bioinformatics, chemical engineering, structural biology, or related fields, Track record of excellence in engineering and research, 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

Nice to Have

GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, dbt Certified

What You'll Do.

Designing and training large-scale machine learning models at the intersection of genomics

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

and research collaborations

How You'll Work.

Team & Collaboration

Mentoring other team members; leading research initiatives; Working closely with hardware and software teams; research collaborations

Communication Scope

publications; presentations

Process & Methodology

craft strategic roadmaps

Full Job Description

The application of modern AI techniques to drug discovery, is radically redefining the field. Genomics, proteomics, molecular dynamics, docking, and protein folding are just some of the areas that are affected. NVIDIA is building an outstanding team to invent the future of foundation models for life sciences. We are seeking senior research scientists and engineers to push the frontier of large-scale foundation models that natively speak the language of cells, biology, and chemistry. The ideal candidate has a strong background in the combination of modern machine learning techniques as applied to drug discovery, genomics, proteomics, or medical chemistry. This is a hands-on role for someone with deep technical expertise and a passion for advancing the state-of-the-art. **What you’ll be doing** * 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 * Mentoring other team members, leading research initiatives, and helping to craft strategic roadmaps * 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 **What we need to see:** * PhD (or equivalent experience) in Computer Science or Computational Biology * 2+ years in deep learning, bioinformatics, chemical engineering, structural biology, or related fields. * Track record of excellence in engineering and research * 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 bi

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