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Date: Wed, 17 May 95 18:09:45 EDT
From: AI.Repository@GLINDA.OZ.CS.CMU.EDU
To: ai+ai-postdoc@cs.cmu.edu
Subject: Postdoc: NLP/Soar at CMU (Pittsburgh, PA)
Sender: ai@A.GP.CS.CMU.EDU

From: Jill Fain <jef+@SARCO.SOAR.cs.cmu.edu>
Subject: Position: Post-doctoral, CMU, NLP/Soar
Date: 27 Apr 1995 13:42:30 GMT

School of Computer Science, Carnegie Mellon University, Pittsburgh, PA

Position: Post-doctoral fellow, effective May 1, 1995.

Contact: Dr. Jill Fain Lehman
         School of Computer Science
         Carnegie Mellon University
         Pittsburgh, PA 15213-3891

         by email: jill.lehman@cs.cmu.edu

Description:  Two-year post-doctoral position working on natural language
processing within the Soar project.  Our main focus will be to extend the
current models of comprehension and generation (NL-Soar) within the context
of military simulations.  In particular, the current system is oriented
toward real-time dialog behavior between intelligent agents (e.g. pilot,
wing, air controller) participating in simulated engagements in the tactical
air domain. Although this work will continue under the current position, we
will also be responsible for providing a real-time, incremental language
capability between these agents and command level agents also built within
the Soar framework.

The natural language project consists of 1 faculty member, 3 graduate
students and a post-doc. In addition to the applications mentioned above,
current research using NL-Soar includes issues in language acquisition,
speech recognition, and simultaneous translation. The language project
exists within a larger Soar community (about 15 members at CMU, about 100
active researchers throughout the world). A post-doctoral fellow is expected
to make significant contributions to the design and implementation of the
system, as well as contribute to the intellectual life of the community.

Qualifications: Applicants should have a Ph.D. in computer science or
computational linguistics. THIS IS A SYSTEM-BUILDING POSTDOC, so a very
strong background in building systems is required.  Experience in both
language generation and comprehension is preferred. Basic knowledge of
machine learning techniques helpful.

To apply: send a resume and names of three references to physical or
e-mail address above. Please have recommendations letters specifically
address the system building strengths and weaknesses of the applicant.

CMU is an Equal Opportunity, Affirmative Action Employer.



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