CZI: Accelerating and Scaling Biological Sciences With AI

Overview

This RFA (Request for Applications) invites applications to build large scale AI/ML models using compute power on CZI's high-performance computing cluster to power new approaches to biological discovery. Applications will be accepted on a rolling basis until June 18, 2025, or until all resources have been allocated. This is an in-kind award; there are no cash funds, financial contributions, or fees of any kind associated with the award.

Award period and start date: Applications should be submitted for projects with a maximum duration of one year. Resource-allocation award period and start date will be dependent on project scope and will be determined by CZI and the grantee once the project is selected for an award

Details

The Chan Zuckerberg Initiative (CZI) invites proposals to build large-scale models that cannot be created with conventional university resources. Through competitive allocation of computing power on CZI’s new GPU cluster, we will support inspired and cutting-edge model building that will power new approaches to biological discovery. Priority will be given to models that align with CZI’s work to build virtual cells in partnership with the scientific community, but all proposals relating to CZI’s mission to cure, prevent, or manage all diseases by the end of the century will be considered.

CZI’s vision is to build the future of science by advancing biomedical research and leveraging advances in AI. Over the next 10 years, we’re working to understand the mysteries of the cell and how cells interact within systems, which will underpin discoveries that will improve medicine in the decades that follow. CZI is the only philanthropic organization to fund and build one of the largest computing systems dedicated to nonprofit life sciences research in the world. CZI is making this cluster available to academic researchers across the U.S. through this RFA.

CZI’s vision demands that progress in biology accelerates. Consequently, we are leveraging the potential of AI to build virtual cell models: multi-scale, multi-modal, large neural network-based models that can represent and simulate the behavior of molecules, cells, and tissues across diverse states to help scientists explore the molecular underpinnings of human health and disease. We foresee virtual cells as having broad applications for biomedical research, disease diagnosis, and therapeutic development.

CZI values open science. Successful proposals must commit to code and weight sharing in accordance with CZI’s data, publication, dissemination, and other applicable policies and principles. We are not supporting models trained on Protected Health Information, and any human data in the training datasets must be de-identified. Grantees will be subject to applicable privacy and security requirements and guidelines to ensure that cluster utilization occurs in a safe and compliant manner.

Our Resource

CZI’s cluster is a leading-edge resource optimized for the performance and scalability required by AI workloads, thus providing the flexibility and power required to accelerate innovation. The cluster is a CoreWeave GPU cloud-based cluster, designed for advanced workloads, featuring 1,024 Nvidia H100 GPUs in a DGX SuperPod configuration with access to VAST fast data storage optimized for AI and machine learning training at scale. The CoreWeave GPU cloud architecture features a fully managed Kubernetes environment that provides bare metal access for performance and the ability to scale workloads optimally. The cluster uses Vast Data’s flash memory (QLC) NVMe SSDs-based storage system to eliminate data access and storage bottlenecks across the AI and data lifecycle. The cluster is actively used to develop and improve cell models on CZI’s prototype virtual cells platform.

This RFA aims to support your most audacious biomedical science powered by AI/ML, with the smallest GPU allocation request to be considered at 96 GPUs. This grant is for an allocation of CZI’s GPU resource (minimum request of 96 GPUs). This is an in-kind award; there are no cash funds, financial contributions, or fees of any kind associated with the award.

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Learn More and Get Started

• To read the full details for this opportunity and to apply, click here

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CZI: How We Support Science

Is it possible to cure, prevent or manage all diseases by the end of this century? We think so. In the last 100 years, biomedical science has made tremendous strides in understanding biological systems, advancing human health, and treating disease, but much more can be achieved in the years to come.

We build open source software tools and leverage artificial intelligence to accelerate the pace of biomedicine. We fund scientific research worldwide to advance the frontiers of knowledge. And we launched a family of institutes to do research that can’t be done in conventional environments. Each aspect is essential to our approach to building for the long term.

Learn more here: https://chanzuckerberg.com/science/

Get in touch: sciencegrants@chanzuckerberg.com

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