PhD positions in DFG Graduate School AIPHES, TU Darmstadt: Deep
Learning for Structured Summaries and Abstractive Summarization
The Research Training Group “Adaptive Information Preparation from
Heterogeneous Sources” (AIPHES) [1], which has been established in
2015 at Technische Universität Darmstadt and at Ruprecht Karls
University Heidelberg is filling two positions for three years,
starting as soon as possible, located in Darmstadt and associated with
UKP Lab (Prof. Iryna Gurevych). Positions remain open until filled.
The positions provide the opportunity to obtain a doctoral degree with
an emphasis in
natural language processing tasks such as structured summaries of
complex contents, abstractive summarization, or a related area.
Applicants should be willing to work on cross-lingual, cross-modality
and domain-independent methods. Prior experience in transfer learning,
multi-task learning, adversarial learning, deep reinforcement learning
or related methods is a plus.
The goal of AIPHES is to conduct innovative research in knowledge
acquisition on the Web in a cross-disciplinary context. To that end,
methods in computational linguistics, natural language processing,
machine learning, computer vision, and data and information management
will be developed. AIPHES investigates a novel,
complex scenario for information preparation from heterogeneous
sources. It interacts closely with end users who prepare textual
documents in an online editorial office, and who should therefore
benefit from the results of AIPHES. In-depth knowledge in one of the
above areas is desirable but not a prerequisite.
AIPHES emphasizes close contact between the students and their
advisors with regular joint meetings, a co-supervision by professors
and younger scientists in the research groups, and an intensive
exchange as part of the research and qualification program.
Participating research groups at Technische Universität Darmstadt are
Knowledge Engineering (Prof. Fürnkranz), Ubiquitous Knowledge
Processing (Prof. Gurevych, Dr. Claudia Schulz), Machine Learning
(Prof. Kersting), Visual
Inference (Prof. Roth), Algorithmics (Prof. Weihe). Participants at
Ruprecht Karls University Heidelberg are the Institute for
Computational Linguistics (Prof. Frank) and the Natural Language
Processing Group (Prof. Strube) of the Heidelberg Institute for
Theoretical Studies (HITS). AIPHES strives to publish its results at
leading
scientific conferences and is actively supporting its doctoral
researchers in this endeavor. The software that will be developed in
the course of AIPHES should be put under the open source Apache
Software License 2.0 if possible. Moreover, the research papers and
datasets should be published with open access models.
Prerequisites
We are looking for exceptionally qualified candidates with a degree in
Computer Science, Machine Learning, NLP, or a related study
program. We expect the ability to work independently, personal
commitment,
team and communication abilities, as well as the willingness to
cooperate in a multi-disciplinary team. Prior experience in
scientific work is a plus. We specifically invite
applications of women. Among those equally qualified, handicapped
applicants will receive preferential consideration. International
applications are particularly encouraged.
The research environment is excellent. The Department of Computer
Science of TU Darmstadt [2] is regularly
ranked among the top ones in respective rankings of German
universities. UKP Lab is a highly dynamic research group committed to
top-level conferences, technologies of the highest standards,
cooperative work style and close interaction of team members [3]. Its
BMBF-funded Centre for the Digital Foundation of Research in the
Humanities, Social, and Educational Sciences (CEDIFOR) emphasizes NLP,
machine learning and text mining. The large-scale argument mining
project allows searching large document collections in response to a
user-defined topic: neural networks determine relevant pro and con
arguments in real-time, and represent them in a concise summary. [4]
Applications should include a motivational letter that refers to one of
the planned research areas of AIPHES [1], 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. Application materials must be submitted via the
following form by June, 27th, 2018:
https://public.ukp.informatik.tu-darmstadt.de/aiphesrecruitment/
In addition, applicants should be prepared to solve a programming and
a reviewing task in the first two weeks after their application.
[1] http://www.aiphes.tu-darmstadt.de/ (cf. Guiding Themes B1, B2)
[2] https://www.informatik.tu-darmstadt.de/
[3] https://www.ukp.tu-darmstadt.de
[4] http://www.argumentext.de/