Xerox Research Intern, Heuristic Search and Planning in North Carolina
Research Intern, Heuristic Search and Planning
City: Palo Alto, Cary
State/Province: California, North Carolina
Country: United States
Department: Student Programs
Date: Friday, January 29, 2021
Working time: Full-time
Job Level: Individual Contributor
Job Type: Internship
Job Field: Student Programs
Description & Requirements
PARC, a Xerox company, is in the Business of Breakthroughs®. Practicing open innovation, we provide custom R&D services, technology, expertise, best practices, and intellectual property to Fortune 500 and Global 1000 companies, startups, and government agencies and partners. We create new business options, accelerate time to market, augment internal capabilities, and reduce risk for our clients. Since its inception, PARC has pioneered many technology platforms – from the Ethernet and laser printing to the GUI and ubiquitous computing – and has enabled the creation of many industries. Incorporated as an independent, wholly owned subsidiary of Xerox in 2002, PARC today continues the research that enables breakthroughs for our clients' businesses
The Knowledge Representation Area at PARC has need for an intern with experience in heuristic search. The area has three ongoing projects that contain heuristic search components. In the DARPA SAIL-ON program, PARC is creating new methods for learning agents to respond to novelties in simulated environments (e.g., adapting strategies to new types of birds in Angry Birds). In the DARPA COMBAT program, PARC is creating new techniques to constrain the automatic generation of courses of action in military planning based on knowledge learned from automatically processing doctrinal documents. In the DARPA NOMARs program, PARC is creating automatic diagnostic and reconfiguration methods to enable extended operation of unmanned ships. The internship will match the intern with the project that best matches their abilities. A successful internship will result in papers at major AI conferences and patent applications.
Currently pursuing a MS or PhD degree in Computer Science, Cognitive Science, HCI, Information and Data Science, or related fields.
Successfully completed beginning-graduate coursework in AI.
Proven record of scientific investigation as demonstrated by project reports, conference presentations, publications (e.g., AAAI, IJCAI, ICAPS, SOCS)
Experience in programming in Python or LISP and in software engineering.
Experience in empirical evaluation for complex intelligent agents.
Experience with PDDL+ planning, parameter estimation, Modelica modeling, and/or hierarchical planning.
Experience with complex agent design methods with hybrid ML and AI reasoning modules is a plus.
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