Nvidia Senior Applied Research Scientist Bioinformatics 

United States, Texas 

939663151

We are building a team of innovative researchers at the intersection of computation, biology, and technology. You will drive the development of computational frameworks and tools that push the boundaries of what’s possible in biological discovery acting as both innovator and strategist: identifying areas where biological progress is limited by informatics challenges, and creating transformative solutions that open new frontiers. This role requires both technical mastery in bioinformatics and the ability to think like a principalinvestigator—formulating

What You'll Be Doing:

• Lead applied and collaborative research programs using bioinformatics, high performance computing, and deep learning for biological advancements.

• Develop and accelerate bioinformatics software and algorithms to garner understanding in biology through data analysis and machine learning applications using NVIDIA's platform.

• Partner with pioneering TechBio startups and academic collaborators to develop, incorporate, and evaluate the future of NVIDIA's accelerated solutions.

• Collaborate across fields with biologists, computer and machine learning scientists to tackle complex biological problems.

• Contribute to scientific strategy in digital biology through publications, conference attendance, and thought leadership.

What We Need To See:

• 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, with the ability to work effectively in multi-functional teams.

• Proven skill in composing, initiating, and implementing impactful research programs independently.

• Expertise in one or more areas of digital biology, such as structural biology, molecular dynamics, or 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 From The Crowd:

• Experience with NVIDIA's 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 in deploying research projects as open-source software and contributing to scientific communities.