Senior Applied Research Scientist, Bioinformatics

at Nvidia
📍 Santa Clara, United States
USD 148,000-287,500 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Algorithms @ 4 Machine Learning @ 4 Data Science @ 6 Leadership @ 4 Mathematics @ 6 Parallel Programming @ 4 Data Analysis @ 4 CUDA @ 4 GPU @ 4

Details

NVIDIA is using the power of high-performance computing and AI to accelerate digital biology. The team works at the intersection of computation, biology, and technology to develop computational frameworks and tools that push the boundaries of biological discovery. This role combines technical mastery in bioinformatics with the ability to lead research directions, build tools, and collaborate across disciplines.

Responsibilities

  • Lead applied and collaborative research programs using bioinformatics, high performance computing, and deep learning to enable biological advancements.
  • Develop and accelerate bioinformatics software and algorithms to derive biological understanding through data analysis and machine learning on NVIDIA's platform.
  • Partner with TechBio startups and academic collaborators to develop, incorporate, and evaluate accelerated solutions.
  • Collaborate with biologists, computer and machine learning scientists to address complex biological problems.
  • Contribute to scientific strategy in digital biology through publications, conference attendance, and thought leadership.

Requirements

  • 5+ years of experience in computer science, physics, mathematics, data science, chemistry, biology, or a related field.
  • PhD or equivalent experience.
  • Excellent collaboration and interpersonal skills; ability to work effectively in multifunctional teams.
  • Proven ability to compose, initiate, and implement impactful research programs independently.
  • Expertise in one or more areas of digital biology (examples: structural biology, molecular dynamics, virtual screening).
  • Experience with high-performance computing infrastructure, parallel programming, and GPU acceleration.
  • Proficiency in crafting libraries for processing biological data through efficient implementations in C or equivalent.

Ways to Stand Out

  • Experience with NVIDIA GPU and AI technologies such as CUDA, cuDNN, and TensorRT.
  • Deep familiarity developing accelerated libraries integrating biological data formats (e.g., PDB, SMILES, FASTA), databases (e.g., NCBI, UniProt, GenBank), and algorithms (e.g., Smith-Waterman, Needleman-Wunsch).
  • Experience deploying research projects as open-source software and contributing to scientific communities.

Compensation & Benefits

Additional Information

  • Applications for this job will be accepted at least until October 19, 2025.
  • NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.