Web Intelligence, Text Mining and Social Media Analytics
(PhD Candidate and Postdoctoral Research Positions)
Position Announcement (PDF, 590 kb)
Participate in award-winning international research projects and become part of a young and interdisciplinary team. You will closely work together with other researchers with a passion for conceptualizing and implementing novel solutions to challenging technical problems. You will collaboratively advance the state of the art in one or more of the following disciplines:
Web Intelligence, Natural Language Processing, Text Mining,
Knowledge Extraction, Visual Analytics, Semantic Search, Linked Data.
The Department of New Media Technology of MODUL University Vienna and the Research Institute for Computational Methods of Vienna University of Economics and Business offer PhD Candidate and Postdoctoral positions. Additional information on related research projects is available at www.decarbonet.eu, www.pheme.eu, www.ucomp.eu and www.weblyzard.com/research.
- Strong Analytical Skills and Extensive Software Development Experience
- Documented Research Track Record and Project Experience (for Postdoctoral Positions)
- Excellent Written and Spoken English (German is not a requirement)
Desired Qualifications :: Focus Area 1, Metrics and Visual Analytics
- Dashboards for Information Exploration and Web Intelligence Applications
- Decision Support and Communication Success Metrics
Desired Qualifications :: Focus Area 2, Natural Language Processing
- Sentiment Analysis and Opinion Mining
- NLP Methods such as POS Tagging, Named Entity Recognition, Dependency Parsing, etc.
- Affective and Factual Knowledge Extraction with Semantic Technologies
The positions remain open until filled (salary levels follow the guidelines of the Austrian Science Fund). MU Vienna and VUEB are equal opportunity employers and strongly encourage qualified women to apply. Please send your complete application including cover letter, curriculum vitae and academic transcript to email@example.com (in English or German; preferably as a single PDF file not exceeding 8 MB).