The Ubiquitous Knowledge Processing (UKP) Lab at the Department of
Computer Science, Technische Universität (TU) Darmstadt, Germany has
an opening for a
PostDoc / Senior Researcher
(for an initial term of two years with an option for an extension)
to strengthen the group’s expertise in the area of Natural Language
Processing with its novel applications to Humanities, Social and
Educational Sciences with a focus on multimodal analysis and
large-scale knowledge extraction. The UKP Lab is a research group
comprising over 30 team members who work on various aspects of Natural
Language Processing (NLP). The group has a strong research profile in
computational linguistics, machine learning and text mining. Core
research areas include semantic text analysis and resources with their
applications in multimodal information processing, knowledge
discovery, and discourse analysis. The lab closely cooperates with
groups in machine learning, image analysis, and interactive data
analytics of the Computer Science department and a large number of
research labs worldwide.
We ask for applications from candidates in Computer Science with a
specialization/PhD in Natural Language Processing or Text Mining,
preferably with expertise in research and development projects and
strong communication skills in English and German (optional). The
successful applicant will work on research and development activities
within the profile area described above and – based on the previous
experience and qualification – will be given an opportunity to
contribute to teaching courses, PhD student co-supervision, and
project management activities.
Ideally, the candidates should have demonstrable experience in NLP
research, designing and implementing complex (NLP and/or ML) systems,
applying Machine Learning incl. neural networks to text processing
(e.g. document classification, sequence classification, clustering,
etc.), information retrieval and databases, scalable data processing,
and strong programming skills in Python and/or Java.
The research environment is excellent. The Department of Computer
Science of TU Darmstadt is regularly ranked among the top ones among
the German universities. Its unique Centre for the Digital Foundation
of Research in the Humanities, Social, and Educational Sciences
(CEDIFOR) and the Research Training Group “Adaptive Information
Processing of Heterogeneous Content” (AIPHES) funded by the DFG
emphasize NLP, machine learning and text mining. UKP Lab is a highly
dynamic research group committed to high-quality research results,
technologies of the highest standards, cooperative work style and
close interaction of team members.
Applications should include a detailed CV, a motivation letter and an
outline of previous working or research experience and the names of
three referees. Applications from women are particularly encouraged.
All other things being equal, candidates with disabilities will be
given preference. Please submit your application via the following
form by November 25, 2017:
https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The
position is open until filled.
Computer Science, Technische Universität (TU) Darmstadt, Germany has
an opening for a
PostDoc / Senior Researcher
(for an initial term of two years with an option for an extension)
to strengthen the group’s expertise in the area of Natural Language
Processing with its novel applications to Humanities, Social and
Educational Sciences with a focus on multimodal analysis and
large-scale knowledge extraction. The UKP Lab is a research group
comprising over 30 team members who work on various aspects of Natural
Language Processing (NLP). The group has a strong research profile in
computational linguistics, machine learning and text mining. Core
research areas include semantic text analysis and resources with their
applications in multimodal information processing, knowledge
discovery, and discourse analysis. The lab closely cooperates with
groups in machine learning, image analysis, and interactive data
analytics of the Computer Science department and a large number of
research labs worldwide.
We ask for applications from candidates in Computer Science with a
specialization/PhD in Natural Language Processing or Text Mining,
preferably with expertise in research and development projects and
strong communication skills in English and German (optional). The
successful applicant will work on research and development activities
within the profile area described above and – based on the previous
experience and qualification – will be given an opportunity to
contribute to teaching courses, PhD student co-supervision, and
project management activities.
Ideally, the candidates should have demonstrable experience in NLP
research, designing and implementing complex (NLP and/or ML) systems,
applying Machine Learning incl. neural networks to text processing
(e.g. document classification, sequence classification, clustering,
etc.), information retrieval and databases, scalable data processing,
and strong programming skills in Python and/or Java.
The research environment is excellent. The Department of Computer
Science of TU Darmstadt is regularly ranked among the top ones among
the German universities. Its unique Centre for the Digital Foundation
of Research in the Humanities, Social, and Educational Sciences
(CEDIFOR) and the Research Training Group “Adaptive Information
Processing of Heterogeneous Content” (AIPHES) funded by the DFG
emphasize NLP, machine learning and text mining. UKP Lab is a highly
dynamic research group committed to high-quality research results,
technologies of the highest standards, cooperative work style and
close interaction of team members.
Applications should include a detailed CV, a motivation letter and an
outline of previous working or research experience and the names of
three referees. Applications from women are particularly encouraged.
All other things being equal, candidates with disabilities will be
given preference. Please submit your application via the following
form by November 25, 2017:
https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The
position is open until filled.