Nvidia Senior Applied Research Scientist Multiscale Biology 

United States, Texas 

121472269

What You'll Be Doing:

• 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.

What We Need To See:

• 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 and contribute to innovation and impact in digital biology and drug discovery.

Ways To Stand Out From The Crowd:

• 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.