Postdoc hiring season at Flatiron

Every year, in the Center for Computational Mathematics at Flatiron Institute, we hire 7 to 10 postdocs to keep up our steady state of roughly 20 postdocs (more and more of them are leaving after 1–2 years to go to industry). Here’s the job ad for this year, with applications due on the absurdly early date of November 15, 2026 (we’re still playing catch-up with plans that make postdoc offers early December):

• Flatiron Research Fellow job application.

The 12-month salary is US$95K plus a US$10K research budget, way better compute resources than most universities have (e.g., hundreds of H100 GPUs which you can actually use), and exceptional benefits (not only free lunch and breakfast, but also great medical care and retirement plans, which has extreme variance among employers in the US). The positions are three years (technically two, with a one year renewal, but nobody has ever been denied a renewal in the 6 years I’ve been here).

Our center is split into three primary research areas, each of which has a web page describing the people and research areas:

• ML and statistics
• structural and molecular biophysics
• numerical analysis and scientific computing

I’m here, as are Steve Bronder and Brian Ward, two software engineers who spend a lot of their time working on Stan, along with other great software engineers (like Jeff Soules and Jeremy Magland who built the Stan Playground with Brian and also MCMCMonitor), and perhaps most importantly, a really engaged and lively group of postdocs working on inference (largely from a diffusion or normalizing flow perspective). This place is great for collaboration both internally and externally.

The postdocs are really fellowships—it’s not like American academia where I get a grant and hire you to work on the grant. You can really work on whatever you want that’s on mission as a postdoc here. So let me recall our mission, which actually matches what we do:

The mission of the Flatiron Institute is to advance scientific research through computational methods, including data analysis, theory, modeling and simulation.

Of all the places I’ve worked over the last 40 years, Flatiron is by far the best. There’s not even a close second. And I’ve been lucky in having great jobs with top notch colleagues (prof at CMU, researcher at Bell Labs, industrial researcher and software engineer writing production code, research scientist at Columbia, then here).

We’re also in a great location—the Flatiron neighborhood of New York City, which is a 10 minute walk to NYU, 10 minute walk to Google and Meta, and 20 minute subway ride to Columbia. Baruch College, the CUNY graduate center, and Fordham’s Manhattan campus are all nearby, and Yale, Rutgers, and Princeton are all in day-trip distance with lots of collaboration.

We’ve had great postdocs, so perhaps not surprising they’ve gotten good jobs: industrial ML jobs at Anthropic, OpenAI, Nvidia, and DataBricks, and stats faculty jobs at Duke University, Johns Hopkins University, the University of Texas, and the University of British Columbia. And that’s just the ML/stats side of our postdocs.

If you want pretty pictures of our setting, check out my job ad from 2021.

If you’re going to be applying in the area of Bayesian modeling or inference, please contact me directly so I don’t miss your application (we got nearly 300 applications for postdocs last year!): bcarpenter@flatironinstitute.org.