Senior Applied AI Researcher, Digital Biology

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

NVIDIA is seeking an Applied AI Researcher to focus on deep learning for biological data, developing foundational, generative, and agentic AI models. The role involves publishing research and contributing to real-world projects in computational medicine and healthcare.

What you'd actually do

  1. Conceptualize, build, and implement novel deep learning architectures for biological data. Focus on large-scale models like Large Language Models (LLMs), Transformers, and State Space Models (SSMs).
  2. Develop multimodal learning systems that integrate heterogeneous data types (e.g., clinical time-series, imaging, genomics, and text) for improved representation and prediction.
  3. Develop both foundational and generative models along with agentic AI systems, encompassing multi-step reasoning, tool use, and autonomous decision-making abilities.
  4. Develop digital twin systems for healthcare by integrating mechanistic models, physiological data, and AI to simulate disease progression, treatment response, and patient-specific trajectories.
  5. Implement deep learning systems coordinated with agents, enabling end-to-end workflows that combine learning, planning, and execution.

Skills

Required

  • deep learning
  • machine learning
  • applied science
  • computational medicine
  • large-scale models
  • LLMs
  • Transformers
  • SSMs
  • multimodal learning
  • heterogeneous data types
  • agentic AI systems
  • multi-step reasoning
  • tool use
  • autonomous decision-making
  • digital twin systems
  • mechanistic models
  • physiological data
  • AI
  • deep learning systems
  • agents
  • end-to-end workflows
  • learning
  • planning
  • execution
  • model performance evaluation
  • results analysis
  • distributed training
  • high-quality code
  • training
  • optimizing
  • deploying large-scale models
  • complex datasets
  • Python
  • C++
  • PyTorch
  • CUDA

Nice to have

  • experience with agentic AI frameworks or systems
  • RAG
  • planning-based agents
  • multi-agent systems
  • data pipelines
  • distributed frameworks for LLM-scale data
  • bioinformatics
  • digital biology
  • developing or deploying digital twin systems
  • simulation frameworks
  • data-driven modeling in healthcare

What the JD emphasized

  • proven record of research success
  • substantial expertise in machine learning
  • publication record required
  • publish your work
  • proven history of publications and presentations at leading conferences

Other signals

  • develop foundational and generative AI models
  • develop agentic AI systems
  • publish your work
  • deep learning architectures for biological data