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Xerox Member of The Research Staff, Artificial Intelligence in North Carolina

Member of The Research Staff, Artificial Intelligence

General information

City: Palo Alto, Cary

State/Province: California, North Carolina

Country: United States

Department: Research & Development

Date: Thursday, March 18, 2021

Working time: Full-time

Ref#: 20010718

Job Level: Individual Contributor

Job Type: Experienced

Job Field: Research & Development

Description & Requirements

PARC is looking for an exceptional candidate who can contribute to the theory and practice of the design of cyberphysical (combination of mechanical, electrical, software, …) systems. We are particularly interested in research which takes a description of a desired function and outlines a plan for the manufacture of an assembly of custom and off-the-shelf parts to achieve this function. The custom parts may be constructed through additive or subtractive methods. Projects include continuing work with various government agencies (e.g., DARPA, DOE, NIST) and Xerox funded AI technology in Digital Design and Manufacturing, IoT, and AI applications. The candidate will be working in a team of over a dozen researchers in AI and Design.


  • Research, design, develop, and implement innovative approaches, methods, and algorithms.

  • Publish results in conferences and file patents

  • Work with internal and external collaborators to formulate problems and define requirements

  • Develop research plans and write proposals

  • Contribute to projects within PARC utilizing 3D manufacturing technology


  • Ph.D. in Mechanical Engineering, Electrical Engineering, Computer Engineering, Artificial Intelligence, or related discipline

  • A typical candidate would have a Ph.D. in Artificial Intelligence with extensive knowledge of engineering, or aa Ph.D. in Mechanical Engineering with extensive knowledge of Artificial Intelligence (both symbolic and machine learning)

  • Demonstrated expertise in physics-based modeling and simulation, control, machine learning, and optimization (both traditional and AI-inspired), e.g. strong publication record

  • Demonstrated implementation skills, including expertise in Python and Matlab.

  • Research mindset and ability to contribute to writing proposals

  • Self-starting: Can work independently within a multi-disciplinary team

  • Experience in reading scientific papers and replicating methods

  • Familiarity with modern software tools and practices

  • Familiarity with generative and combinatorial design

  • Knowledge of Modelica is a plus

  • Familiarity with functional languages is a plus.


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