Google Cloud for Researchers

Make tomorrow’s research breakthroughs possible. Accelerate your research with training, free credits, and resources from Google Cloud.

Apply for credits

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Researchers at USC use Google Cloud to accelerate the drug discovery process

Explore the benefits

Submit a proposal to receive up to $5,000 in free Google Cloud credits for academic research. Use Google's high performance computing capabilities.

Get started with Google Cloud by accessing free online training through Google Cloud Skills Boost and applying for learning credits from the platform.

Connect to a community of peers doing breakthrough research. Share ideas through online communities or apply to be a Google Cloud Research Innovator.

Learn Google Cloud

Get access to the Google Cloud catalog in Google Cloud Skills Boost for hands-on practice. Apply to receive up to 200 credits. Share credits with students and track lab completion.

Research Discipline	Overview	Training
Research, development, and prototyping	RAD Lab Discover RAD Lab, a Google Cloud-based sandbox environment to help teams advance quickly from research and development to production.	GitHub - Explore Rad Lab's code repository
High performance computing	HPC Subscription With Google Cloud's HPC Subscription, researchers can ramp up their projects quickly, regardless of their technical expertise level—at a fixed subscription price, avoiding overage costs.	Tutorial - Using the Slurm Resource Manager to host Jupyter notebooks Codelab - Deploy an auto-scaling HPC cluster with slurm
Environmental sciences	Image processing Using large-scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition.	Codelab - Train and deploy on-device image classification with AutoML Vision Google Cloud Skills Boost - Classify images of clouds with AutoML Vision
Environmental sciences	Flower image classification using Keras on TPUs Learn how to build, train, and tune your own convolutional neural networks from scratch with Keras and TensorFlow.	Codelab - Using TPU-speed data pipelines: tf.data.Dataset and TFRecords Codelab - Modern convnets, squeezenet, Xception, with Keras and TPUs
Life sciences	Genomics With Cloud Life Sciences (formerly Google Genomics), learn to process biomedical data at scale.	Tutorial - Genomic data processing reference architecture Video - Genomic Analyses on Google Cloud
Life sciences	Healthcare Cloud Healthcare API provides a managed solution for storing and accessing healthcare data in Google Cloud, providing a critical bridge between existing care systems and applications hosted on Google Cloud.	Google Cloud Skills Boost - Ingesting FHIR Data with the Healthcare API Course - Cloud Healthcare API
Social sciences	Cloud AI Platform Get hands-on practice with TensorFlow 2.x model training, both locally and on AI Platform. After training, you will learn how to deploy your model to the AI Platform for serving (prediction).	Google Cloud Skills Boost - Vertex AI Workbench Notebook: Qwik Start
Social sciences	Machine learning APIs Get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API.	Google Cloud Skills Boost - Intro to ML: Language Processing
Physical sciences	Image analysis and classification The Cloud Vision API lets you understand the content of an image by encapsulating powerful machine learning models in a simple REST API. Send images to the Vision API and see it detect objects, faces, and landmarks.	Google Cloud Skills Boost - Detect Labels & Landmarks with the Cloud Vision API
Mathematical sciences	Financial services Google Cloud machine learning techniques, especially deep learning, hold great promise for time series analysis. As time series become more dense and begin to overlap, machine learning offers a way to separate the signal from the noise.	Tutorial - Analyzing portfolio risk using HTCondor and Compute Engine
	Data science Apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud.	Codelab - Run a Big Data Text Processing Pipeline in Cloud Dataflow Google Cloud Skills Boost - Vertex AI Workbench Notebook: Qwik Start
	Jupyter, R, and RStudio Perform large-scale technical computing on Google Cloud.	Tutorial - Data science with R on Google Cloud: Exploratory data analysis tutorial
Computer science	Media and rendering Learn how to deploy the OpenCue render management system on Linux virtual machines (VMs) using Google Cloud.	Tutorial - Creating a render farm in Google Cloud using OpenCue
	Workload managers Learn to optimize utilization and efficiency through workload managers that simplify cluster administration.	Video - Google Cloud Workload Manager
	Containers and kubernetes Learn to use a managed environment to focus on experiencing Kubernetes rather than setting up the underlying infrastructure.	Tutorial - Deploying containerized workloads to Slurm on Compute Engine Google Cloud Skills Boost - Orchestrating the Cloud with Kubernetes
	MapReduce - Hadoop/Spark Create Cloud Dataproc clusters quickly and resize them at any time so you don't have to worry about your data pipelines outgrowing your clusters.	Google Cloud Skills Boost - Intro to Cloud Dataproc: Hadoop and Spark Codelab - Provisioning a Managed Hadoop/Spark Cluster with Cloud Dataproc
	Remote desktop and visualization Learn to set up a Chrome Remote Desktop service or a virtual Linux workstation.	Tutorial - Setting up Chrome Remote Desktop for Linux on Compute Engine Tutorial - Creating a virtual GPU-accelerated Linux workstation
	Lustre Access enterprise-class DDN EXAScaler Lustre software through the Google Cloud Marketplace and an open sourced set of scripts to easily configure and deploy a Lustre storage cluster on Compute Engine.	Codelab - Deploy a Lustre Parallel File System on Google Cloud
	Generative AI training Learn the fundamentals of Large Language Models and Google Cloud generative AI solutions.	Google Cloud Skills Boost - Self-paced training on curated generative AI content

Learn Google Cloud

Research, development, and prototyping

RAD Lab

Discover RAD Lab, a Google Cloud-based sandbox environment to help teams advance quickly from research and development to production.

GitHub - Explore Rad Lab's code repository

High performance computing

HPC Subscription

With Google Cloud's HPC Subscription, researchers can ramp up their projects quickly, regardless of their technical expertise level—at a fixed subscription price, avoiding overage costs.

Tutorial - Using the Slurm Resource Manager to host Jupyter notebooks
Codelab - Deploy an auto-scaling HPC cluster with slurm

Environmental sciences

Image processing

Using large-scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition.

Codelab - Train and deploy on-device image classification with AutoML Vision
Google Cloud Skills Boost - Classify images of clouds with AutoML Vision

Life sciences

Genomics

With Cloud Life Sciences (formerly Google Genomics), learn to process biomedical data at scale.

Tutorial - Genomic data processing reference architecture
Video - Genomic Analyses on Google Cloud

Social sciences

Cloud AI Platform

Get hands-on practice with TensorFlow 2.x model training, both locally and on AI Platform. After training, you will learn how to deploy your model to the AI Platform for serving (prediction).

Google Cloud Skills Boost - Vertex AI Workbench Notebook: Qwik Start

Physical sciences

Image analysis and classification

The Cloud Vision API lets you understand the content of an image by encapsulating powerful machine learning models in a simple REST API. Send images to the Vision API and see it detect objects, faces, and landmarks.

Google Cloud Skills Boost - Detect Labels & Landmarks with the Cloud Vision API

Mathematical sciences

Financial services

Google Cloud machine learning techniques, especially deep learning, hold great promise for time series analysis. As time series become more dense and begin to overlap, machine learning offers a way to separate the signal from the noise.

Tutorial - Analyzing portfolio risk using HTCondor and Compute Engine

Computer science

Media and rendering

Learn how to deploy the OpenCue render management system on Linux virtual machines (VMs) using Google Cloud.

Tutorial - Creating a render farm in Google Cloud using OpenCue

Join the community

All researchers who received Google Cloud credits are added to our online researcher community. Researchers can also apply for the Research Innovator program.

Researcher community

Join fellow faculty and researchers who are using Google Cloud in their labs and in their classrooms. Only researchers who have been verified and approved to receive Google Cloud credits are eligible to join. Please check your onboarding email for a link to join; or request access using your school-issued email address.

Join the online community

Research Innovators

Apply to join a global community of researchers driving scientific breakthroughs with Google Cloud. Research Innovators gain access to professional development and other benefits. We are not accepting applications now, but you can learn more about the program, meet the inaugural cohort, and request to be notified when applications open.

Learn about the program