Postdoctoral Scientist , Amazon Robotics

DESCRIPTION The Amazon Robotics Research, Applied, and Data Science team is looking for a talented Postdoctoral Scientist to join our team for a one-year, full-time research position.
This postdoctoral scientist will conduct research in multi-agent optimization and reinforcement learning for robotic warehouse workflows. They will have the opportunity to address challenges related to the control and optimization of the world's largest fleet of mobile robots under uncertainty, including policy learning for resource management in robotic sortation systems, policy learning for task assignment in robotic storage systems, and planning of tasks for multiple stations with different capabilities to support multiple complex business objectives.
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.
A day in the life
On a typical day in this role you will work to progress your research projects, meet with engineering, systems, and solutions stakeholders, brainstorm with other scientists on the team, and participate in team processes. You will follow your multi-agent optimization and reinforcement learning projects though the entire life cycle of design, implementation, evaluation, analysis, and will communicate your findings and results through publications in top-tier academic venues.
About the team
Our team is a multi-disciplinary science team that includes scientists with backgrounds in planning and scheduling, grasping and manipulation, machine learning, and operations research. We develop novel planning algorithms and machine learning methods and apply them to real-word robotic warehouses, including: (1) Planning and coordinating the paths of thousands of robots (2) Dynamic allocation and scheduling of tasks to thousands of robots (3) Learning how to adapt system behavior to varying operating conditions and (4) Co-design of robotic logistics processes and the algorithms to optimize them.
We are open to hiring candidates to work out of one of the following locations:
North Reading, MA, USA BASIC QUALIFICATIONS Basic qualifications include:
•PhD in a relevant field, received within 2 years of starting the program
•Proven publication record in Machine Learning, Robotics, AI, Computer Science, Operations Research, or other related technical fields
•Experience in data science and quantitative research
•Proficiency in technologies relevant to multi-agent optimization, reinforcement learning, and controls.