Develop and study models for high-dimensional scientific prediction, generation, and design, including: Diffusion models, flow matching, consistency models, score-based generative models, energy-based models, latent-variable models, autoregressive models, and normalizing flows. Have deep expertise in at least two of the following: generative modeling, probabilistic inference, uncertainty quantification, geometric deep learning, graph neural networks, optimization, reinforcement learning/control, numerical methods, scientific machine learning, quantum algorithms, or quantum information.