Overview
This is an exciting opportunity for a PhD candidate at the Institute of Information Systems Engineering at TU Wien, Austria. The position focuses on the semi-automatic labeling of argumentative zones in scientific articles, utilizing reinforcement learning techniques. This research is significant as it aims to enhance the understanding and processing of scientific literature, which is crucial for advancing knowledge in various fields.
Background & Relevance
Natural Language Processing (NLP) is a vital area within artificial intelligence that enables machines to understand and interpret human language. The research on argumentative zoning is particularly relevant as it helps in structuring scientific discourse, making it easier to extract and summarize important information. This PhD project will contribute to the development of tools that can automate the analysis of scientific texts, thereby improving the efficiency of literature reviews and research activities.
Key Details
- University: TU Wien (Technische Universität Wien, Austria)
- Location: Vienna, Austria
- Position: PhD student
- Research Focus: Semi-automatic labeling of argumentative zones using reinforcement learning
- Funding: Secured through the AR-Science project
- Application Deadline: September 20, 2019
- Contact Email: florina.piroi@tuwien.ac.at
Eligibility & Participation
Candidates should hold a Master’s degree in Computer Science. A Master of Arts is acceptable if it is in Language Technology or Computational Linguistics. Applicants should possess foundational knowledge in NLP, experience with annotation and corpus design, and good communication skills in English. Familiarity with distributional semantics is advantageous.
Submission or Application Guidelines
Interested candidates should submit their CV along with a brief cover letter to the provided email address by the application deadline. Ensure that your application highlights relevant experience and skills that align with the research focus of the position.
Additional Context / Real-World Relevance
The AR-Science project aims to create an innovative platform that streamlines the process of scientific publication mining. By automating the handling of scientific information, this research will significantly reduce the time researchers spend on literature searches and reviews. The outcomes of this PhD project could lead to advancements in how scientific knowledge is accessed and utilized, benefiting researchers across various disciplines.
Conclusion
This PhD position at TU Wien represents a valuable opportunity for individuals interested in the intersection of NLP and reinforcement learning. Those who meet the eligibility criteria are encouraged to apply, as this research has the potential to make a meaningful impact in the field of scientific research and publication.
Category: PhD & Postdoc Positions
Tags: nlp, reinforcement learning, tu wien, argumentative zoning, deep learning, scientific publication, corpus design, language technology
