I have appreciated Jessica’s recent coverage of differential privacy and related topics on this blog — especially as I’ve also started working in this general area.

So I thought I’d share this new postdoc position that Manish Raghavan and I have here at MIT where it is an important focus. Here’s some of the description of the broad project area, which this researcher would help shape:

This research program is working to understand and advance techniques for sharing and using data while limiting what is revealed about any individual or organization. We are particularly interested in how privacy-preserving technologies interface with recent developments in high-dimensional statistical machine learning (including foundation models), questions about fairness of downstream decisions, and with causal inference. Applications include some in government and public policy (e.g., related to US Census Bureau data products) and increasing use in multiple industries (e.g., tech companies, finance).

While many people with relevant expertise might be coming from CS, we’re also very happy to get interest from statisticians — who have a lot to add here!

This post is by Dean Eckles.