Applied Research Phd Student, Foundation Models for Materials Science

NVIDIA NVIDIA · Semiconductors · Tel Aviv, Israel

NVIDIA is seeking a PhD student for joint research at Bar-Ilan University on next-generation Foundation Models for Materials Science. The role involves developing novel multi-modal foundation models, leveraging large-scale data, representation learning, and uncertainty estimation, with a focus on publishing results in top-tier venues.

What you'd actually do

  1. Conduct research in deep learning and AI for materials science, with a focus on foundation models, multi-modal learning, and representation learning.
  2. Develop and train large-scale models for materials discovery and prediction tasks.
  3. Collaborate with researchers and engineers across NVIDIA and academia.
  4. Lead independent research under academic supervision, while contributing to team efforts.
  5. Publish results in top-tier conferences and journals, and present findings clearly and effectively.

Skills

Required

  • Ph.D. student
  • Master’s degree (M.Sc.)
  • Strong background in deep learning and machine learning
  • Experience with foundation models, multi-modal learning, or self-supervised learning
  • Strong communication skills
  • Ability to work collaboratively in interdisciplinary teams

Nice to have

  • Background or strong interest in materials science and chemistry
  • Proven experience in building or training large-scale foundation models
  • Experience with uncertainty estimation, generative models, or scientific machine learning
  • Strong programming skills in Python and deep learning frameworks (e.g., PyTorch)

What the JD emphasized

  • publication track record

Other signals

  • foundation models
  • multi-modal learning
  • representation learning
  • materials discovery