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Postdoctoral Position on Information-theoretic Foundations of Generative Models
Postdoctoral position at ASU on topics at the intersection of information and learning theory to rigorously understand the working of generative adversarial networks. Ideal candidate has a PhD in EE/Stats and a solid background in information theory.

Prof. Lalitha Sankar in the School of Electrical, Computer, and Energy Engineering at Arizona State University is looking for a postdoctoral fellow to work on topics at the intersection of information and learning theories in the context of generative adversarial networks (GANs). An ideal candidate will have a PhD in EE, CS or IE with a strong background in optimization, information theory, and/or statistical learning theory. Familiarity with functional analysis is desirable as the work will explore such connections.

Interested candidates should contact Prof. Sankar at [email protected] with CV and a list of publications. This position is funded by the National Science Foundation and Simon Foundation’s Mathematics of Deep Learning program.

Arizona State University is the largest public school in the United States. Its ECEE department is ranked in the top 25 in the country. It also boasts of world-famous faculty in the areas of optimization, communications, signal processing, information theory, and statistical learning theory.