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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New research led by Flatiron Institute researchers reveals the source of the mysterious swirling flows in some of nature’s largest cells.
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.
Initiatives
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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- CCN
- CCA
- CCB
- CCQ
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.
- CCB
- CCM
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
An adaptive spectral method for oscillatory second-order linear ODEs with frequency-independent cost
We introduce an efficient numerical method for second-order linear ODEs whose solution may vary between highly oscillatory and slowly changing…
SIAM Journal on Numerical AnalysisCombining machine learning with structure-based protein design to predict and engineer post-translational modifications of proteins
Post-translational modifications (PTMs) of proteins play a vital role in their function and stability. These modifications influence protein folding, signaling,…
PLOS Computational BiologyNuclear instance segmentation and tracking for preimplantation mouse embryos
For investigations into fate specification and cell rearrangements in live images of preimplantation embryos, automated and accurate 3D instance segmentation…
bioRxivNews & Announcements
April 24, 2024
April 17, 2024