18 September: fyi -- phd funding, Germany

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Group (Prof. Ulf Brefeld, http://www.uni-bonn.de/~brefeld/) at
Technical University of Darmstadt, Germany.

The position's focus will be on machine learning, data mining, and
information retrieval, particularly on unsupervised information
extraction and aggregation. Duties and responsibilities include
teaching as well as academic research. The group closely collaborates
with the German Institute for International Educational Research
(DIPF) in Frankfurt/Main (http://www.dipf.de) and is part of the
research initiative for Knowledge Discovery in the Web
(http://www.werc.tu-darmstadt.de/).

Requirements:
The candidate should have or expect to obtain a MSc or equivalent in computer science, mathematics, or physics.

Desirable skills:
* profound knowledge of kernel machines, structured input-output spaces, graphical models, and probabilistic inference
* strong mathematical skills
* practical experience with automatic web crawlers
* expertise in natural language processing and information extraction
* practical experience of processing data at internet scales using Hadoop/MapReduce
* strong programming skills
* good written and spoken communication skills in German or English.

The position is a fixed-term contract with an option to extend it,
provided certain conditions are met. We offer the possibility of
further scientific qualification towards a doctoral degree. The salary
is based on TV-TU Darmstadt (standard for employees at TU
Darmstadt). A part-time working arrangement is possible.

The Department of Computer Science of TU Darmstadt is regularly ranked
among the best in Germany. We invite applications from women and
people with disabilities. More informations (in German):
http://www.intern.tu-darmstadt.de/dez_vii/stellen/stellen_details_80832.de.jsp

Inquiries should be directed to
stegmann@tk.informatik.tu-darmstadt.de. Applications (reference number
351) should be addressed to the Dean of the Department of Computer
Science, Hochschulstr. 10, 64289 Darmstadt, Germany. Deadline:
September 23.

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