Amazon’s research teams are looking forward to meeting you at ICLR 2019. Come and visit us at the Amazon booth, and read on for more information about academic collaboration, career opportunities, and our teams.

• Orals
  • "Transferring Knowledge across Learning Processes" Authors: Sebastian Flennerhag, Pablo Moreno, Neil D Lawrence, Andres Damianou
• Publications
  • "Bayesian Policy Optimization for Model Uncertainty" Authors: Gliwoo Lee, Brian Hou, Aditya Mandalika, Jeongseok Lee, Sanjiban Choudhury, Siddhartha Srinivasa
  • "Learning to Navigate the Web" Authors: Izzeddin Gur, Ulrich Rueckert, Aleksandra Faust, Dilek Hakkani-Tur
  • "Learning What and Where to Attend" Authors: Drew Linsley, Dan Shiebler, Sven Eberhardt, Thomas Serre
  • "Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet" Authors: Wieland Brendel, Matthias Bethge
  • "L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data" Authors: Jianbo Chen, Le Song, Martin Wainwright, Michael Jordan
  • "The Limitations of Adversarial Training and the Blind-Spot Attack" Authors: Huan Zhang, Hongge Chen, Zhao Song, Duane S Boning, Inderjit Dhillon, Cho-Jui Hsieh
  • "Passage Ranking with Weak Supervision" Authors: Xu Peng, Xiaofei Ma, Ramesh Nallapati, Bing Xiang. ICLR Workshop on Learning from Limited Labeled Data
  • "Weakly-Semi-Supervised Neural Topic Models" Authors: Ian Gemp, Ramesh Nallapati, Ran Ding, Feng Nan, Bing Xiang. ICLR Workshop on Learning from Limited Labeled Data

Amazon and NSF Collaborate to Accelerate Fairness in AI Research

NSF and Amazon are partnering to jointly support computational research focused on fairness in AI, with the goal of contributing to trustworthy AI systems that are readily accepted and deployed to tackle grand challenges facing society. NSF has long supported transformative research in artificial intelligence (AI) and machine learning (ML). The resulting innovations offer new levels of economic opportunity and growth, safety and security, and health and wellness. 

Check out the details here. 

re:MARS 2019

Artificial intelligence is changing every industry. Join us at Amazon re:MARS, a new global AI event on Machine Learning, Automation, Robotics, and Space, to learn why and how to apply the latest AI advances in your business and work. re:MARS is inspired by MARS, an event hosted by Jeff Bezos that brings together leading minds to advance a golden age of innovation. re:MARS is your opportunity to participate, combining the latest in forward-looking science with practical applications. 

Internships for PhD Students

We offer 3-6 month internships year-round, with opportunities in Aachen, Atlanta, Austin, Bangalore, Barcelona, Berlin, Boston, Cambridge, Cupertino, Graz, Haifa, Herzliya, Manhattan Beach, New York, Palo Alto, Pasadena, Pittsburgh, San Francisco, Shanghai, Seattle, Sunnyvale, Tel Aviv, Tübingen, Turin, and Vancouver. To apply, email your resume to ICLR2019@amazon.com, and let us know if there are any specific locations, teams, or research leaders that you are interested in working with. 

Job Opportunities for Graduating Students and Experienced Researchers

We are looking for results-driven individuals who can apply advanced machine learning techniques, love to work with data, are deeply technical, and highly innovative. If you long for the opportunity to invent and build solutions to challenging problems that directly impact the way Amazon transforms the consumer experience, we are the place for you. To apply, email your resume to ICLR2019@amazon.com, and let us know if there are any specific locations, teams, or research leaders that you are interested in working with. 

Publishing at Amazon

Amazon is committed to innovating at the frontiers of machine learning and artificial intelligence. Our scientists are encouraged to engage in the research community in the form of written publications, open source code and public datasets. We have instituted a new, fast-track publication approval process, to help share our research efforts as quickly as possible, while maintaining the highest standards of quality.

Amazon Web Services (AWS) Research Grants

In partnership with Machine Learning@Amazon, AWS offers up to $20,000 in compute tokens each quarter to professors and students. Academics have used these grants for projects ranging from Hack End weekends to massive MRI imaging projects. AWS provides building blocks for developing applications ranging from Elastic MapReduce for Hadoop analytics to fast and scalable storage with Amazon DynamoDB. Learn more & apply here.

Amazon Research Awards

ARA is an unrestricted gift to recognize exceptional faculty, and fund projects leading toward a PhD degree or conducted as a part of post-doctoral work. Each selected proposal is assigned an Amazon research contact, as we believe that both sides benefit from direct interaction on the topic of their research. We invite ARA recipients to visit Amazon offices worldwide to give talks related to their work and meet with our research groups face-to-face. We encourage ARA recipients to publish the outcome of the project and commit any related code to open source code repositories. Learn more here.

Alexa Prize

The Alexa Prize is an annual competition for university students dedicated to accelerating the field of conversational AI. Learn more at alexaprize.com.

Diversity at Amazon

We are a company of builders working on behalf of a global customer base. Diversity is core to our leadership principles, as we seek diverse perspectives so that we can be “Right, A Lot”. We welcome people from all backgrounds and perspectives to innovate with us. Learn more at amazon.com/diversity.

Amazon Scholars

Amazon Scholars is a new program for academic leaders to work with Amazon in a flexible capacity, ranging from part-time to full-time research roles. Learn more at amazon.jobs/scholars.

Amazon is an Equal Opportunity Employer.