Open Postdoctoral position, faculty mentor Madeleine Udell

The Udell Group at Stanford University is seeking a highly motivated and independent postdoctoral fellow to join our research team working on optimization and deep learning. This position offers a unique opportunity to work on cutting-edge research in a supportive and collaborative environment.

Topics of interest include:

Optimization for Machine Learning:

• Preconditioning methods for large-scale and stochastic optimization.
• Efficient deep learning using low rank and compressed representations.
• Applications to scientific machine learning and engineering design.

Learning for Optimization:

• Deep reinforcement learning for combinatorial optimization. 
• Automated optimization modeling using large language models in combination with traditional optimization techniques.  Scope includes accurate modeling, user interface, eliciting values, trust and verification, efficiency of the representation, automated relaxations, decompositions, and approximations, choice of solver and hyperparameters, and automatically designing a custom solver.
• Applications to classic OR problems such as scheduling, routing, supply chain.

Automated Data Science:

• Automatically develop new trustworthy models using large language models + tools from interpretable or causal machine learning.
• Applications to healthcare problems such as diagnosis, treatment planning, and disease prediction for heart disease, diabetes, etc.

Beyond the topics above, we're excited to explore other ideas with the potential for big impact in optimization, deep learning, and data science.