Frequently asked questions

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In addition to the FAQs below, please view the ARA Program Rules.

General program information

What types of proposals does ARA fund?
The Amazon Research Awards (ARA) program funds academic research and related contributions to open-source projects by top academic researchers around the world. ARA aims to fund projects leading toward a PhD degree or conducted as a part of post-doctoral work.

Is the AWS Machine Learning Research Awards (MLRA) program part of ARA?
Yes, in 2020 the two programs merged and MLRA now funds awards through ARA, under the AWS AI call for proposal.

What is the structure of an ARA award? Can it be extended?
Awards are structured as one-year unrestricted gifts to the Principal Investigator's academic institution or organization, and can include cash and AWS Promotional Credits. Though this funding is not extendable, applicants can submit new proposals for subsequent calls.

What research areas does ARA fund?
ARA funds in a variety of research areas relevant to Amazon, such as applied machine learning, automated reasoning, computer vision, fairness in artificial intelligence, machine learning algorithms and theory, natural language processing, robotics, security, and more. Please refer to the detailed CFPs for more information.

Applying for an award

Who is eligible to apply?
Researchers from around the world are encouraged to apply. Please refer to the ARA Program Rules for eligibility.

How do I apply?
Please follow the instructions on the specific CFP you are applying to.

What are the timelines for proposal submissions and decisions?
We evaluate research proposals and provide decisions via email to all applicants approximately three months after the submission deadline. Please follow the timeline on the specific CFP you are applying to.

What is an Amazon contact and is one required to apply?
An Amazon contact is an Amazon employee who is aware of the proposal, familiar with the Principal Investigator’s research and may be willing to serve as an Amazon research contact for the proposal, if it is selected. An Amazon contact is not required to submit a proposal. While the ARA team is not able to provide an Amazon contact for the PI prior to submission, all funded proposals will be assigned an Amazon research contact by the review panel.

Is it possible to have multiple faculty members on a single proposal?
Each proposal should be submitted by a single faculty member, who will also supervise the student or post-doc who is to be funded by the award. Other members of the research team can and should be mentioned in the proposal.

Is it possible for one faculty member to be on multiple grants?
Principle Investigators can only submit one proposal at each deadline. Your proposal can be considered for a second CFP with the same deadline, if it meets the scope of both CFPs. Please follow the instructions when you are submitting your proposal.

What budget expenses will Amazon consider for the award?
A proposed cash budget is generally expected to support one or two PhD students (or a post-doctoral researcher) for one year, plus some conference travel and equipment. The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel. Please refer to the CFP for specific budget guidelines.

Additionally, proposals may include a request for AWS Promotional Credits1. Proposals should include the requested amount, a short justification, a list of AWS products and any AWS Public Datasets to be used in the proposed research. The final amount of free AWS Promotional Credits will be determined by the awards panel.

Proposal review process

Who will evaluate the proposals and when will I know the outcome of the review?
Project proposals are reviewed by an internal awards panel and the results are communicated approximately three months after the submission deadline. We will communicate the decision to the primary PI listed on each proposal, and will make an announcement on the ARA website. We expect the primary PI to notify the rest of their team about funding decisions.

Will I be able to find out why my proposal was not accepted?
Unfortunately, due to the number of proposals we receive, we are unable to provide detailed reasons a proposal was not accepted.

Award information

What happens after the ARA recipients are announced?
Each project will be assigned an Amazon research contact. The researchers are encouraged to maintain regular communication with their Amazon contact to discuss ongoing research and project progress. We also encourage publishing the outcome of the project and committing any related code to open-source code repositories.

Does Amazon retain any intellectual property and licensing on the material developed during the time period that a student is funded?
ARA funding is distributed as unrestricted gifts to universities. As such, the funding does not result in any transfer or license of any intellectual property rights. Please refer to the ARA Program Rules for more information.

Do recipients have access to Amazon data?
Recipients will have access to Amazon datasets that are already public, such as the Amazon Bin Image Dataset, but not to non-public data.

Does Amazon accept any legal obligation with respect to submitted proposals?
We are happy to review non-confidential project proposals. As such, project proposals shall not contain any confidential information (please do not include any information in your proposal that you or others consider confidential). Amazon does not accept any legal obligation (whether of confidentiality, compensation, return or otherwise) with respect to any proposals. Amazon reserves the right to implement similar ideas in the future without restriction or obligation. Please refer to the ARA Program Rules for more information.

Additional information

May I speak to someone from the Amazon Research Awards team to find out more?
We provide limited email support via research-awards@amazon.com. Due to the volume of emails we receive, we may not be able to respond to questions where the answer is available on the website.

Can I be added to upcoming CFP announcements?
Yes, please email research-awards@amazon.com to be added to the quarterly CFP email announcement.

Are there any other funding opportunities offered by Amazon?
Yes, please visit the Academic Engagements page for more information. Note that the AWS Machine Learning Research Awards program is part of ARA.

1 Please note that your use of any AWS Promotional Credit is subject to the general AWS Customer Agreement terms or other terms governing your use of AWS Services (“Agreement”). In the event of a conflict between these Rules and the Agreement, the Agreement will control with respect to your access to and use of the Service Offerings. Additionally, any use of AWS Promotional Credit will be in accordance with and subject to the AWS Promotional Credit Terms & Conditions. In the event of a conflict between these Rules and the AWS Promotional Credit Terms & Conditions, the AWS Promotional Credit Terms & Conditions will govern with respect to any AWS Promotional Credit you receive.

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Applied Scientist II
US, WA, Seattle
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Economist
US, WA, Seattle
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Economist
US, VA, Arlington
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Sr. Data Scientist
US, NY, New York
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Research Scientist
US, WA, Seattle
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Senior Applied Scientist
US, WA, Seattle
Amazon’s High Value Messaging (HVM) Analytics team (part of Customer Behavior Analytics) is looking for a Senior Applied Scientist to spearhead the rapid growth of our Marketing Measurement solutions. The team focuses on building scalable scientific models to estimate the effectiveness of Amazon marketing efforts and provide actionable insights to the various marketing teams within Amazon. We are looking for a thought leader that has an aptitude for delivering customer-focused solutions and who enjoys working on the intersection of Big-Data analytics, Machine/Deep Learning, and Causal Inference.A successful candidate will be a self-starter, comfortable with ambiguity, able to think big and be creative, while still paying careful attention to detail. You should be able to translate how data represents the customer journey, be comfortable dealing with large and complex data sets, and have experience using machine learning and econometric modeling to solve business problems. You should have strong analytical and communication skills, be able to work with product managers and software teams to define key business questions and work with the analytics team to solve them. You will join a highly collaborative and diverse working environment that will empower you to shape the future of Amazon marketing, as well as allow you to be part of the large science community within the Customer Behavior Analytics (CBA) organization.The Customer Behavior Analytics (CBA) organization owns Amazon’s insights pipeline, from data collection to deep analytics. We aspire to be the place where Amazon teams come for answers, a trusted source for data and insights that empower our systems and business leaders to make better decisions. Our outputs shape Amazon product and marketing teams’ decisions and thus how Amazon customers see, use, and value their experience.The main responsibilities for this position include:· Apply expertise in ML and causal modeling to develop systems that describe how Amazon’s marketing campaigns impact customers’ actions· Own the end-to-end development of novel scientific models that address the most pressing needs of our business stakeholders and help guide their future actions· Improve upon and simplify our existing solutions and frameworks· Review and audit modeling processes and results for other scientists, both junior and senior· Work with marketing leadership to align our measurement plan with business strategy· Formalize assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them· Identify new opportunities that are suggested by the data insights· Bring a department-wide perspective into decision making· Develop and document scientific research to be shared with the greater science community at Amazon
ML Applied Scientist
US, CA, San Diego
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by protecting Amazon customers from hackers and bad actors? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer every day? Are you excited by the prospect of analyzing and modeling terabytes of data and create state-of-art algorithms to solve real world problems? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Amazon Account Integrity team.The Amazon Account Integrity team works to ensure that customers are protected from bad actors trying to access their accounts. Our greatest challenge is protecting customer trust without unjustly harming good customers. To strike the right balance, we invest in mechanisms which allow us to accurately identify and mitigate risk, and to quickly correct and learn from our mistakes. This strategy includes continuously evolving enforcement policies, iterating our Machine Learning risk models, and exercising high‐judgement decision‐making where we cannot apply automation.
ML Applied Scientist
US, CA, San Diego
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by protecting Amazon customers from hackers and bad actors? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer every day? Are you excited by the prospect of analyzing and modeling terabytes of data and create state-of-art algorithms to solve real world problems? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Amazon Account Integrity team.The Amazon Account Integrity team works to ensure that customers are protected from bad actors trying to access their accounts. Our greatest challenge is protecting customer trust without unjustly harming good customers. To strike the right balance, we invest in mechanisms which allow us to accurately identify and mitigate risk, and to quickly correct and learn from our mistakes. This strategy includes continuously evolving enforcement policies, iterating our Machine Learning risk models, and exercising high‐judgement decision‐making where we cannot apply automation.
Applied Scientist II #0000
US, CA, San Francisco
LOCATION: San Francisco, CAMULTIPLE POSITIONS AVAILABLE1. Analyze real user data (search query logs) using SQL or equivalent data query language.2. Train machine learning / deep learning based models using ML platforms and libraries such as Tensorflow, Pytorch, Pyspark etc.3. Apply natural language processing techniques to improve ranking of search results and develop new ranking features and techniques building upon the latest results from the academic research community4. Boost search conversion by classifying user search queries and recommending relevant content5. Contribute to operational excellence in search team's scientific features, constructively identifying inefficient processes and proposing solutions6. Experiment with different models, analyze results using statistical methods and iterate on improving the results7. Propose and validate hypotheses to direct our business and product road map. Work with engineers to make low latency model predictions and scale the throughput of the system.8. Design, develop, and implement production level code that serves millions of search requests. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment.9. Telecommuting benefits available#0000
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