Programming job: text mining in ancient texts

Marco Büchler at the University of Leipzig just sent around this announcement:

The Natural Language Processing Division at the Computer Science Department of the  University of Leipzig, Germany, is the leading partner in the E-Humanties project eAQUA –  a project financed by the German Ministry of Research and Technology for applying  advanced text mining technology to digital ancient texts (www.eaqua.net).

For this project we are searching for computer scientist with demonstrated research expertise  in one or more of the following areas:

• Experience in Text Mining and Natural Language Processing,
• Programming skills in Java with applications in the E-Humanties,
• Processing of large digital text resources.

Prior experience in participating in large European or other transnational initiatives is highly  desirable.

The starting date for this full-time position is February 1, 2009. The initial period of  appointment is for two years, with the possibility of renewal subject to follow-up funding.
The position is at the rank of “Wissenschaftlicher Mitarbeiter” (M.A. or equivalent required).  The salary is determined by the German civil servants standard (Entgeltgruppe 13 TV-L) and  amounts to 42000-52000 Euro per year. The exact salary depends on the successful  applicant’s experience.

Applications should include CV, an outline of research experience, as well as names and  addresses of references. Applications should be sent by mail or by email to the address below.

Prof. Dr. Gerhard Heyer
Automatische Sprachverarbeitung
Institut für Informatik
Universität Leipzig
Postfach 10
D – 04009 Leipzig
Germany
email: heyer@informatik.uni-leipzig.de

Applications received by January 31, 2009 will receive full consideration, although interviews  may start at any time and will continue until the position has been filled.

Disabled applicants will be preferred if they have the same qualifications as non-disabled  applicants. The University of Leipzig strives to increase the proportion of women in research  and teaching, and therefore encourages qualified female scientists to apply.