NVIDIA is seeking to accelerate digital biology by developing next-generation technological solutions to identify technology bottlenecks in multiscale biology and invent novel applied solutions that unlock better biological discovery and understanding.
Requirements
- Experience with scaled computing, such as high-performance computing, parallel programming, and GPU acceleration applied to omics data at scale.
- Deep familiarity with experimental biology and assay design, coupled with strong computational, algorithmic, or software engineering skills.
- Scientific track record developing and implementing technologies for biological data learning or analysis (e.g., imaging analysis, simulation frameworks, large-scale data integration, machine learning biological data) with NVIDIA's GPU and AI technologies, such as CUDA, cuDNN, and TensorRT.
- Track record of building impactful tools, platforms, and open-source software for life sciences.
- Experience in deploying research projects as open-source software and contributing to scientific communities.
- Scientific experience in functional genomics.
- 5+ years of experience in biology, computer science, data science, physics, chemistry, mathematics, or a related field.
Responsibilities
- Conduct collaborative applied research in multiscale biology using deep learning and high-performance computing to identify critical biological challenges and experimental limitations.
- Develop and optimize algorithms, software tools, and machine learning models for applications such as large scale genomics or proteomics analysis using NVIDIA's platform.
- Disseminate work demonstrating the technological impact of new capabilities on advancing biological research via open source releases and publications.
- Partnering with software engineers, data scientists, and product teams to envision and realize tools and infrastructures that redefine digital biology!
- Apply your expertise in engineering biology through algorithms and tools for genes, tissues, organisms, and populations.
- Work across disciplines with biologists, chemists, and machine learning scientists to tackle complex biological problems.
- Engage and collaborate with leaders with a point of view in industry and academia to promote NVIDIA's Digital Biology solutions.
Other
- PhD or equivalent experience
- Proven ability to build and manage relationships with the ecosystem of scientific partners in industry and academia.
- Superb communication and collaboration skills, with the ability to work effectively in multi-functional teams.
- A commitment and contribute to innovation and impact in digital biology and drug discovery.
- Applications for this job will be accepted at least until October 20, 2025.
