Overview

The recently established Research Training Group „Adaptive Information
Preparation from Heterogeneous Sources“ (AIPHES) at the Technische
Universität Darmstadt and at the Ruprecht-Karls-University Heidelberg
fills a position for three years as a PhD-level Researcher in Natural
Language Processing.

The position provides an opportunity to obtain a doctoral degree in
natural language processing with the focus on “Structured summaries of
complex contents”. Thereby, the candidate will have a chance to research
methods operating on large-scale corpora to extract hidden language-based
structures that allow the users to effectively navigate the information
space. The project will utilize both linguistic notions from computational
linguistics and the most recent developments in computer science methods,
such as graph-based methods, ranking methods, or deep learning. Through a
set of cooperations in the areas of large-scale databases,
high-performance computing and distributed systems, we aim to develop a
real-time, scalable NLP system for structuring continuous text streams on
the Web. The position is situated in the Computer Science Department of
the Technische Universität Darmstadt and is affiliated with the
Ubiquitous Knowledge Processing (UKP) Lab, Prof. Dr. Iryna Gurevych. The
funding follows the guidelines of the German Research Foundation (DFG),
and the positions are paid according to the E13 public service pay scale.

The goal of AIPHES is to conduct innovative research in a
cross-disciplinary context. To that end, methods in computational
linguistics, natural language processing, machine learning, network
analysis, and automated quality assessment are jointly developed. AIPHES
investigates a novel scenario for information preparation from
heterogeneous sources, within the application context of multi-document
summarization. There will be close interaction with end users who prepare
textual documents in an online editorial office, and who should therefore
profit from the results of AIPHES.

 

Prerequisites
We are looking for exceptionally qualified candidates with a degree in
Computer Science, Computational Linguistics, or a related study program.
We expect ability to work independently, personal commitment, team and
communication abilities, as well as the willingness to cooperate in a
multi-disciplinary team. Desirable is experience in scientific work.
Applicants should be able to work with German-language texts, and, if
necessary, to acquire German language skills during the training program.
We specifically invite applications of women. Among those equally
qualified, handicapped applicants will receive preferential consideration.
International applications are particularly encouraged.

The Department of Computer Science of TU Darmstadt is regularly ranked
among the top ones in respective rankings of German universities. Its
unique research initiative “Knowledge Discovery in the Web” emphasizes
natural language processing, text mining, machine learning, as well as
scalable infrastructures for assessment and aggregation of knowledge. The
Institute for Computational Linguistics (ICL) of the
Ruprecht-Karls-University Heidelberg is one of the large centers for
computational linguistics both in Germany and internationally. The ICL and
the NLP department of the HITS jointly run the graduate program „Semantic
Processing“ with an integrated research training group “Coherence in
language processing: Semantics beyond the sentence”, which has a close
connection to the topics in computational linguistics of AIPHES.

Applications should include
* a motivational letter that refers to the above described research theme,
* a CV with information about the applicant’s scientific work,
* certifications of study and work experience,
* as well as a thesis or other publications in electronic form.

They should be submitted until August 18th, 2015 to the spokesperson of
the research training group, Prof. Dr. Iryna Gurevych (Fachbereich
Informatik, Hochschulstr. 10, 64289 Darmstadt) using the e-mail address
jobs@ukp.informatik.tu-darmstadt.de.

 

 

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