Amazon is looking for talented Postdoctoral Scientists to join our Robotics team for a one-year, full-time research position. Postdoctoral Scientists will innovate in key areas of computer vision and manipulation challenges in Amazon warehouses.
The Amazon Robotics team seeks to automate the picking activities in Amazon AR Sortable FCs by retrofitting into existing stations. The team develops robotic manipulators, both the related hardware and software (including machine learning approaches). The team was formed in 2022 and is based in Berlin.
Our team focuses on solving computer vision and manipulation challenges in Amazon warehouses. For example, how can robots interact with the fabric pods used to store items. The technical challenges include 3D scene understand for items in clutter, identification of target items in the scene, and placement and/or removal of target items. As the solution space is open ended, the team is looking for postdoc candidates who are excited to apply and advance the state-of-the-art algorithms to this domain.
Key job responsibilities
In this role you will:
• Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community.
• Publish your innovation in top-tier academic venues and hone your presentation skills.
• Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.
BASIC QUALIFICATIONS
* PhD in a relevant field, received within 2 years of starting the program
* Proven publication record in computer vision, robotics or other related technical fields #
* Experience in item perception and manipulation
* Proficiency in technologies relevant to the subfield
PREFERRED QUALIFICATIONS
• Ability to independently deliver results in a fast-paced environment
• Publications at top-tier, peer-reviewed conferences and/or journals
• Exceptional verbal and written communication skills
• Expert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies