Postdoctoral Scientist , Amazon Robotics
North Reading, Massachusetts
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:
• \tWork closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon's vibrant and diverse global science community.
• \tPublish your innovation in top-tier academic venues and hone your presentation skills.
• \tBe 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:
• \tPhD in a relevant field, received within 2 years of starting the program
• \tProven publication record in Machine Learning, Robotics, AI, Computer Science, Operations Research, or other related technical fields
• \tExperience in data science and quantitative research
• \tProficiency in technologies relevant to multi-agent optimization, reinforcement learning, and controls.
PREFERRED QUALIFICATIONS
Postdocs demonstrate the following preferred job qualifications:
• \tAbility to independently deliver results in a fast-paced environment
• \tPublications at top-tier, peer-reviewed conferences and/or journals
• \tExceptional verbal and written communication skills
• \tExpert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies
Required application materials:
• \tCV, which lists all peer-reviewed publications and conferences,
• \tResearch statement that outlines your research achievements and future research interests, and
• \tA journal article or book chapter that demonstrates your domain expertise.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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:
• \tWork closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon's vibrant and diverse global science community.
• \tPublish your innovation in top-tier academic venues and hone your presentation skills.
• \tBe 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:
• \tPhD in a relevant field, received within 2 years of starting the program
• \tProven publication record in Machine Learning, Robotics, AI, Computer Science, Operations Research, or other related technical fields
• \tExperience in data science and quantitative research
• \tProficiency in technologies relevant to multi-agent optimization, reinforcement learning, and controls.
PREFERRED QUALIFICATIONS
Postdocs demonstrate the following preferred job qualifications:
• \tAbility to independently deliver results in a fast-paced environment
• \tPublications at top-tier, peer-reviewed conferences and/or journals
• \tExceptional verbal and written communication skills
• \tExpert knowledge in modeling and performance, operationalization, and scalability of scientific techniques and establishing decision strategies
Required application materials:
• \tCV, which lists all peer-reviewed publications and conferences,
• \tResearch statement that outlines your research achievements and future research interests, and
• \tA journal article or book chapter that demonstrates your domain expertise.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Created: 2024-06-01
Reference: 2656516
Country: United States
State: Massachusetts
City: North Reading
About Amazon
Founded in: 1994
Number of Employees: 1600000
Website: https://www.amazon.com/
Career site: https://www.amazon.jobs/en/
Instagram: https://www.instagram.com/amazon/
LinkedIn: https://www.linkedin.com/company/amazon/
Facebook: https://www.facebook.com/Amazon
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