Conduct collaborative applied research in multiscale biology using deep learning and high-performance computing to identify critical biological challenges and experimental limitations.
Work across disciplines with biologists, chemists, and machine learning scientists to tackle complex biological problems.
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.
Engage and collaborate with leaders with a point of view in industry and academia to promote NVIDIA's Digital Biology solutions.
Requirements
PhD or equivalent experience
5+ years of experience in biology, computer science, data science, physics, chemistry, mathematics, or a related field.
Proven ability to build and manage relationships with the ecosystem of scientific partners in industry and academia.
Experience with scaled computing, such as high-performance computing, parallel programming, and GPU acceleration applied to omics data at scale.
Superb communication and collaboration skills, with the ability to work effectively in multi-functional teams.
Deep familiarity with experimental biology and assay design, coupled with strong computational, algorithmic, or software engineering skills.
A commitment to contribute to innovation and impact in digital biology and drug discovery.
Benefits
equity
benefits
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Applicant Tracking System Keywords
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Hard skills
deep learninghigh-performance computingalgorithmssoftware toolsmachine learning modelsparallel programmingGPU accelerationomics data analysisexperimental biologyassay design
Soft skills
communication skillscollaboration skillsrelationship managementteamworkinnovationimpact contribution