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. |
|
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. |
|
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. |
|
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. |
||
Life sciences |
Genomics
With Cloud Life Sciences (formerly Google Genomics),
learn to process biomedical data at scale. |
|
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.
|
|
|
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). |
|
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. |
|
|
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.
|
|
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. |
|
Data science
Apply sophisticated statistical and machine learning
methods to real-world problems when you build on top
of the Google Cloud. |
|
|
Jupyter, R, and RStudio
Perform large-scale technical computing on Google
Cloud. |
|
|
Computer science |
Media and rendering
Learn how to deploy the OpenCue render management
system on Linux virtual machines (VMs) using Google
Cloud. |
|
Workload managers
Learn to optimize utilization and efficiency through
workload managers that simplify cluster
administration. |
|
|
Containers and kubernetes
Learn to use a managed environment to focus on
experiencing Kubernetes rather than setting up the
underlying infrastructure. |
|
|
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. |
|
|
Remote desktop and visualization
Learn to set up a Chrome Remote Desktop service or a
virtual 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. |
|
|
Generative AI training
Learn the fundamentals of Large Language Models and
Google Cloud generative AI solutions. |
|
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
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.
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
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.
Genomics
With Cloud Life Sciences (formerly Google Genomics),
learn to process biomedical data at scale.
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
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
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
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
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 - Running R at Scale on Compute Engine
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.
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
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.
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.
See impact stories
See stories of how researchers around the world are using Google Cloud to accelerate breakthroughs.
"We’re saving time and money by running Flywheel on Google Cloud, but what’s most important is the reproducibility we’re able to achieve. The ability to share our research to benefit people all over the world goes right to the heart of science for me."
Dr. Brian Wandell, Faculty Professor and Director of CNI, Stanford University
Read the full story