Associate Research Scientist (PostDoc- or PhD-level; for an initial term of two years)
This position should further strengthen and develop the profile of the lab in natural language processing (NLP) and related topics such as machine learning, multimodal content analysis, information retrieval, or novel applications of NLP to social sciences and humanities.
Possible areas of research include, but are not limited to:
• interactive clustering and machine learning to extract sets of textual snippets according to multiple criteria, e.g. high-quality and diverse examples illustrating a lexical entry’s usage;
• NLP for low-resource languages, e.g. analyzing discourse-level argumentation in Georgian;
• interactive sequence labeling to support claim validation by experts, e.g. for extracting evidence from corpora;
• joint text and image processing for content classification in social media, e.g. identifying bias;
• analyzing and generating creative language, such as humor, metaphor, or other rhetorical means.
The lab has a strong profile in the above areas, which features robust semantic analysis and textual inference, multimodal content analysis and summarization, and applications of NLP including novel benchmarks and problem definitions. It currently develops a new focus on interactive machine learning and chatbots and conversational agents. The lab closely cooperates with machine learning, computer vision, and data management groups of the Computer Science department. It has a strong industrial network and works together with social sciences and humanities on real-life research problems.
We are looking to attract highly qualified candidates with an outstanding degree in NLP, machine learning, or a related field of Computer Science. The candidates should preferably have research and teaching experience and strong communication skills in English and German (optional). Together with the candidate, we work out an individual career development plan and identify the relevant opportunities for the professional and personal growth within the activities of the lab.
The research environment is excellent. The Department of Computer Science of the TU Darmstadt is regularly one of the top ranked ones among the German universities. Its unique Research Training Group “Adaptive Information Processing of Heterogeneous Content” (AIPHES)†funded by the DFG and the BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences (CEDIFOR) emphasize NLP, machine learning and text mining.† UKP Lab is a very dynamic research group committed to high-profile research, cooperative work style and close interaction of team members.
Applications should include a detailed CV, a motivation letter, an outline of previous working or research experience and the names of ideally 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 September 30th, 2018: https://public.ukp.informatik.tu-darmstadt.de/ukprecruitment. The position is open until filled.
-- Nadezhda Smirnova Ubiquitous Knowledge Processing Lab (UKP-TUDA) Department of Computer Science Technische Universitšt Darmstadt Tel: +49 151 2941 0734 Web: https://www.ukp.tu-darmstadt.de/