application of state-of-the-art data mining and retrieval technology in the context of structural engineering: simulation data mining, domain-specific retrieval, and machine learning technology will help to simplify and integrate complex modeling, design, and simulation tasks.
From:
Date:
At: Bauhaus-Universität Weimar
Location: Weimar, Germany
Web: www.webis.de
The Web Technology and Information Systems Group (www.webis.de) at the Faculty of Media at Bauhaus-Universität Weimar, Germany, is inviting applicants for the position of a research assistant in the fields data mining, machine learning, and information retrieval.
( German version of the job advertisement )
The position is part of an interdisciplinary research project. Research subject is the application of state-of-the-art data mining and retrieval technology in the context of structural engineering: simulation data mining, domain-specific retrieval, and machine learning technology will help to simplify and integrate complex modeling, design, and simulation tasks.
The engagement can start in the third quarter of 2010 (exact date is flexible) and is limited for two years; an extension is possible and expected. In particular, it is possible to do a PhD (Dr. rer. nat.) and will be supported. Salary is based on the collective agreement for public sector in Germany, 13 TV-L.
The candidate should have studied computer science, mathematics, or a related field with excellent or very good grades. A solid background in mathematics and statistics is expected - as well as good programming skills. We are an experienced research group where team spirit and active collaboration is top priority; we are looking for an open-minded graduate who wants to develop himself both as a researcher and a person.
_Contact_:
Interested and qualified candidates are asked to submit the usual documents electronically by July 17th to benno.stein[at]uni-weimar.de.
Postal address:
Bauhaus-Universität Weimar
Faculty of Media
Prof. Dr. Benno Stein
99421 Weimar
Web: www.webis.de
We do not discriminate on the basis of race, religion, color, national origin, gender, age, or disability.
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