PhD Research Intern, Fundamental Generative AI

What you'll do

• Research and design novel large-scale generative AI methods for image, video, 3D, graph, and multimodal data.
• Implement advanced generative models to solve real-world problems in science applications like drug discovery and climate modeling.
• Publish original research findings at top-tier machine learning venues such as NeurIPS, CVPR, and ICLR.
• Develop and prototype new AI technologies using Python and deep learning frameworks like PyTorch.
• Translate and transfer developed technologies to internal product groups for practical application.
• Contribute to the advancement of fundamental generative AI methods across various domains.

What we're looking for

• Must be pursuing a Ph.D. program in Computer Science, Engineering, Statistics, or a related field.
• Must have a strong publication record at top machine learning venues such as NeurIPS, CVPR, ICLR, ICML, ICCV, or ECCV.
• Must possess excellent knowledge of the theory and practice of generative AI.
• Must have strong knowledge of computer vision, 3D, NLP, or AI for science.
• Must have excellent programming skills in rapid prototyping environments such as Python.
• Must have excellent communication skills.
• Knowledge of common deep learning frameworks like PyTorch is required.
• Proficiency in C++ and parallel programming (e.g., CUDA) is preferred.