PhD Applied Scientist, Routing

Exol•Wilmington, MA

46d•$52 - $54•Hybrid

About The Position

Symbotic is seeking an applied scientist intern with a passion for multi-agent planning to enhance the performance and reliability of its systems during rapid product and organizational scaling. The Robot Routing team is responsible for planning highly efficient, collision-free paths for numerous robots operating between the storage structure and the inbound/outbound cells within the system. This role involves working with concepts such as deadlock resolution and time-space reservations. This is a hybrid position located at Symbotic's headquarters in Wilmington, MA, for the Summer (May-Aug 2027) timeframe. Early Career talent at Symbotic contributes to reimagining supply chain automation through internships and co-op programs, offering opportunities to work on real projects, collaborate with experienced professionals, and gain hands-on exposure to robotics and automation technologies. The company seeks curious, motivated students eager to solve complex problems, bring fresh perspectives, and make an impact in an innovative, fast-paced environment. Interns and Co-ops receive support through mentorship, professional development, networking, and a structured calendar of events.

Requirements

Pursuing PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, or a related field.
Proficiency in one or more general-purpose programming languages: C++, Python, Java, or C#.
Strong research background in combinatorial optimization, Robotics planning, multi-robot systems, or machine learning.
Publications at high-impact conferences/journals (e.g., CoRL, ICLR, NeurIPS, ICML, ICLR, RSS, ICRA, IROS, RAL, AAAI, ICAPS, IJCAI, JAIR, etc.) on some of the aforementioned topics.

Responsibilities

Identify high-impact scenarios where AI Planning and machine learning can be applied to optimize the Symbotic robotics software.
Adapt state-of-the-art approaches or develop high-performance algorithms to solve real-world multi-robot problems.
Conduct simulations and experiments to validate the performance of the multi-robot algorithms.
Present results in verbal and written communications internally, and in top-tier academic venues.