Amazon Science Community and Machine Learning University call for proposals - Spring 2022
Making Amazon the best place in the world to do customer-obsessed science and engineering
About this CFP
The Amazon Science Community and Machine Learning University teams are committed to making Amazon the best place in the world to do customer-obsessed science and engineering. Our programs, including onboarding bootcamps, mentorship programs, and instructor-led classes, help Amazon’s scientists and engineers do their best work. We aim to advance the state of the art in the design and execution of these programs. We are seeking to fund economics and social science research on the following topics:
- Scientific productivity metrics – high quality science can take years to develop and have a customer impact; how can we know in the meantime if a research team is flourishing or floundering?
- Scientific impact metrics – scientific work not only operates on long timelines, it has a cumulative effect. One research paper may not get turned into a product or service, but it can serve as critical inspiration for the next research paper that does. How can we assess the impact of a given research project, team, or individual, beyond basic tools like citation and patent metrics?
- Team-based research success factors – impactful science is increasingly done by teams; research teams to create the science, and engineering teams to implement scientific solutions on behalf of customers. What are the most critical factors that cause a team to have scientific success, and what mechanisms can influence them?
- Individual-based research success factors – what are the key factors to individual scientific success, and which of these are a product of the institutional environment? How can we optimize the physical and social environment to allow scientists to do their best work?
- Educational design – what drives success in technical courses when presented in-person, live remote, or self-paced? What drives students to choose one option or the other, and how can we leverage hybrid formats to bring together the strengths of each of these? What are the data-driven best practices for online education, particularly with regards to recent shifts in working practices? How do we measure practical success when teaching scientific knowledge at scale?
Submission period: June 3 - July 8, 2022
Decision letters will be sent out December 2022
Selected Principal Investigators (PIs) may receive the following:
- Unrestricted funds, no more than $80,000 USD
- AWS Promotional Credits, no more than $20,000 USD
- Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers
Awards are structured as one-year unrestricted gifts. 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 ARA Program rules on the FAQ page.
Proposals should be prepared according to the proposal template.
PIs should either include plans for open source contributions or state that they do not plan to make any open source contributions (data or code) under the proposed effort.
ARA will make the funding decisions based on the potential impact to the research community and quality of the scientific content.
Expectations from recipients
To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.