21 May: fyi -- post doc., Stanford
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POSTDOC(S) at STANFORD on LEARNING SEMANTICS FROM TEXT
We have postdoc opportunities for one, or possibly two, people to join
the Stanford NLP group, to work on topics in the general area of
mapping from text to meaning. Particular topics of interest include
mapping from syntactic parse trees to semantic relational structures,
and from there to semantic schemas which support probabilistic
reasoning; syntax-guided information extraction; topics in
probabilistic parsing; and applications of information extraction to
educational resources.
The general approach of interest combines probabilistic models and
modern machine learning methods with a richer representational basis
than has standardly been used in statistical NLP applications. An
ideal applicant would have extensive experience in statistical
approaches to machine learning and NLP, but also some experience of
rich grammar formalisms and semantics/knowledge representation
formalisms. We're also looking for someone with good programming
skills, preferably including Java. These are grant-funded positions,
and the postdoc would need to contribute to project goals. The
postdoc(s) will last for 2 years.
To apply, please send a cover letter, particularly emphasizing
relevant background, project experience, and current research
interests, and your CV, and arrange for 2 or 3 references to be sent
to the address below (post or by email). Informal inquiries can also
be directed to the address below. The position will be open until
filled, but full consideration will certainly be given to any
applications received by the end of June.
More information about NLP at Stanford can be found on the NLP Group
homepage at: http://nlp.stanford.edu/ . Stanford offers unparalleled
opportunities in computer science, and the Stanford NLP group
cooperates closely with other NLP activities at CSLI and at Berkeley.
-
Christopher Manning
Dept of Computer Science, Gates 4A,
353 Serra Mall,
Stanford CA 94305-9040,
USA
E manning@cs.stanford.edu
W +1 (650) 723-7683
F +1 (650) 725-2588
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