We are offering three full-time researcher positions in the field of Machine Learning and Data Mining.
Position 1: E-Democracy & Web Mining
The position belongs to an interdisciplinary research focus „E-Democracy“ at the University of Koblenz-Landau. We aim to understand how the internet affects democracy, how one can support democracy through digitisation, and how one can detect misinformation and violence in political online discourses. More details at http://west.uni-koblenz.de/en/research/e-democracy. The position is available as of now and time-limited to three years. Post-Doc applicants will be given preference for this position.
Position 2: Information Extraction
This position is part of the project „EXCITE – Extraction of Citations from PDF Documents“, funded by the German Research Foundation (DFG). Together with GESIS – Leibniz Institute for the Social Sciences we develop algorithms that extract references and citations from PDF files and match these with bibliographic databases. By this we aim to overcome the lack of citation data in the German and international social sciences. More about EXCITE at http://west.uni-koblenz.de/en/research/excite. The position is available as of now, time-limited until 31st August 2018, and in case of successful extension of the research project it might become extended by two years.
Position 3: Machine Learning & Data Mining
Position no. 3 is part of a research cooperation with an industry partner of WeST. Together we will investigate the potential capabilities of neural networks for various monitoring applications in rail traffic. Details about the intended project can be obtained from Prof. Dr. Steffen Staab (email@example.com). The position is available as of now and time-limited to three years, subject to finalization of the cooperation contract.
We are looking for researchers with a very good master's degree or doctorate from a University (or equivalent). Eligible applicants are interested in many scientific domains, gladly collaborate with colleagues from other scientific disciplines, and can precisely identify and carefully solve computer science-related issues with their well-grounded programming capabilities.
- applicants for position 1 ideally have experience in one of the areas of text and data mining, information extraction, computational linguistics, or computational social science, and they should speak German fluently;
- prospective researchers for position 2 preferably have experience in information extraction or machine learning;
- applicants for position 3 ideally have experience in one oft he areas of machine learning, neural networks, signal processing and must speak German fluently.
Applications submitted before 15th June will be given priority, later applications are possible. Please apply online via https://west.uni-koblenz.de/en/app using one of the following reference numbers:
- position 1: reference number 71/2017 (formerly 35/2017)
- position 2: reference number excite/2017
- position 3: reference number mldm/2017
Questions about the application process can be addressed to firstname.lastname@example.org.
Web Science investigates how the technical structure of the Web affects the activities of its 3.5 billion users and how their manifold interactions stimulate the Web’s technical advancement in return. Founded in 2009, the Institute for Web Science and Technologies (WeST) combines expertise in research and development in computer science, the social sciences, and economy. The institute is part of the computer science faculty, located at the campus in Koblenz at the University of Koblenz-Landau.
We offer a creative, versatile, internationally renowned research environment. We support your scientific curiosity and your doctorate or habilitation. We offer a new campus with an excellent IT infrastructure in one of the most livable cities in Germany.
Das Institut WeST sucht häufiger nach talentierten Hilfskräften, die mehr als ein Semester lang als Studierende im Fachbereich Informatik unserer Universität eingeschrieben sind. Wir bieten Positionen sowohl in der Forschung als auch in der Lehre und bieten die Möglichkeit, Teil eines eingespielten Teams zu werden.
Falls Sie an einer Stelle als studentische Hilfskraft interessiert sind und mindestens im zweiten Semester sind, wenden Sie sich mit einer Beschreibung Ihrer Interessengebiete und Fähigkeiten und einem Lebenslauf an email@example.com.