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Senior Applied AI Researcher, Digital Biology

NVIDIA· Architect
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Hybrid (Tel Aviv, Israel)full-timePosted 6mo ago

About the role

Applied AI researcher role focusing on deep learning for biological data, including foundational and generative models, agentic AI, digital twin healthcare systems, and interdisciplinary collaboration within NVIDIA’s Health Platform ecosystem.

Responsibilities

  • Conceptualize, design, and implement novel deep learning architectures for biological data, with a focus on large-scale models such as LLMs, Transformers, and State Space Models (SSMs)
  • Develop multimodal learning systems that integrate heterogeneous data types (clinical time-series, imaging, genomics, text) for improved representation and prediction
  • Develop both foundational and generative models and agentic AI systems, including multi-step reasoning, tool use, and autonomous decision-making capabilities
  • Develop digital twin systems for healthcare, combining mechanistic models, physiological data, and AI to simulate disease progression, treatment response, and patient-specific trajectories
  • Implement deep learning systems integrated with agents, enabling end-to-end workflows that combine learning, planning, and execution
  • Evaluate model performance, analyze results, and iterate on designs to achieve optimal outcomes
  • Apply knowledge of distributed training to build high-quality code for training, optimizing, and deploying large-scale models, while managing complex datasets
  • Collaborate closely with a diverse team of researchers, bioinformaticians, and domain experts in a highly interdisciplinary environment

Qualifications

  • PhD in Machine Learning, Computer Science, Engineering, or a related discipline
  • 8+ years of hands-on experience in developing, training, and deploying deep learning models at scale, including LLMs, Transformers, SSMs, and/or generative models
  • Experience with multimodal learning and integrating diverse data modalities is highly valued
  • Experience with agentic AI frameworks or systems (e.g., tool-augmented models, planning-based agents, or multi-agent systems) is a strong advantage
  • Strong expertise in distributed training, optimization, and inference
  • Proven ability to lead independent research, implement robust solutions, and rigorously evaluate performance
  • Track record of publications and presentations at top conferences
  • Strong programming skills in Python and C++, with experience in PyTorch and/or CUDA
  • Excellent communication skills and ability to thrive in a dynamic, research-driven team. Mentoring experience is a plus

Skills

Required:Deep learningMultimodal learning
Nice to have:Agentic AI / tool-augmented models

Benefits

  • Equal opportunity employer
  • Diversity and inclusion commitment
  • Reasonable accommodation for applicants with disabilities upon request
Last updated Jul 3, 2026. Interested? Apply on the company site.

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