The mission of the Flatiron Institute is to advance scientific research through computational methods, including data analysis, theory, modeling and simulation.
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By marrying statistical techniques with computational tools, Flatiron Institute research scientist Dan Foreman-Mackey is helping astronomers probe the atmospheres of other planets.
Our Centers
Center for Computational Biology
Center for Computational Mathematics
Center for Computational Neuroscience
Center for Computational Quantum Physics
Scientific Computing Core
It develops, deploys and maintains computational infrastructure — from supercomputers to desktop PCs — dedicated solely to the use of Flatiron researchers.
Collaborative Work

Machine learning has become an indispensable tool for computational science, and it is an active and growing area of research throughout the Flatiron Institute.
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Underlying all biological processes are molecules and their interactions with each other. However, our ability to understand how these molecules function over biologically relevant scales remains very limited.
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This collaboration, directed by Greg Bryan of Columbia University, aims to understand and determine the evolution and initial conditions of our universe, using observations via a Bayesian forward modeling approach.
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- | Columbia University
- | Lawrence Berkeley National Lab
- | Harvard University
- | Stockholm University
- | Institute D'Astrophysique de Paris
- | Université de Montreal
- | Princeton University
- | Carnegie Mellon University
- | Max-Planck Institute for Astrophysics
Flatiron Institute Inclusion, Diversity,
Equity & Advocacy (IDEA) Scholar Program
For distinguished scientists with a particular interest in diversity and inclusion
Scholars may engage in a variety of activities, such as working on scientific projects, starting new collaborations, mentoring junior scientists, and organizing or participating in workshops and career development events.
Software
A major effort of the Flatiron Institute is the development and support of high-quality, open-source software for research.
Research Highlights
Stable Solid Molecular Hydrogen above 900 K from a Machine-Learned Potential Trained with Diffusion Quantum Monte Carlo
We survey the phase diagram of high-pressure molecular hydrogen with path integral molecular dynamics using a machine-learned interatomic potential trained…
Physical Review LettersStable Solid Molecular Hydrogen above 900 K from a Machine-Learned Potential Trained with Diffusion Quantum Monte Carlo
We survey the phase diagram of high-pressure molecular hydrogen with path integral molecular dynamics using a machine-learned interatomic potential trained…
Physical Review LettersEnsemble reweighting using Cryo-EM particles
Cryo-electron microscopy (cryo-EM) has recently become a premier method for obtaining high-resolution structures of biological macromolecules. However, it is limited…
arXiv:2212.05320News & Announcements
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