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Machine Learning Techniques for Conversation Understanding

Palo Alto, CA | internships

Job Description

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.

As one of the most prolific innovation centers in the world, PARC offers an exceptional internship experience. Considered valuable members of our community, interns are fully integrated into the daily activities of PARC's highly collaborative, multidisciplinary culture.

The Augmented Social Cognition group at PARC seeks a talented researcher for a 3 month internship focusing on computational modeling of phone calls from transcribed text. The goal is to develop novel algorithms that advance the state-of-the-art in Machine Learning while  being practical and robust to be used in a real system. The successful candidate should:

  • be pursuing a PhD in computer science, electrical engineering or related disciplines with focus on Machine Learning / Statistical techniques for NLP
  • have strong programming skills in Java and/or Python
  • have deep understanding of graphical models and Bayesian estimation techniques for natural
  • language processing (LDA, CRF's, etc.)
  • have strong presentation and writing skills
  • be creative and have out-of-the-box thinking
  • be excited to work in a multidisciplinary team of very-driven individuals

Please apply with a cover letter and links to relevant work.

For more information on the PARC internship program visit http://www.parc.com/internship

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