The research focus of the MTEC Group is in signal processing and pattern recognition, applied to acoustic, visual, text-based, and multimodal time series. We use concepts and techniques of signal acquisition, signal preprocessing, statistics, information theory, and machine learning to extract information from text, acoustic signals, videos and/or images. This information can, for example, be the semantic categorization of a sentence within a text, the recognition of spoken language in an acoustic signal, or the detection of an anomaly in an image.
We are currently looking for a researcher (wissenschaftliche:r Mitarbeiter:in, TV-L E13, full time) to develop techniques for the recognition of mis- and disinformation in multimodal data, specifically in combinations of text and images. The work is embedded in a collaborative project funded by the Bundesministerium für Bildung und Forschung (BMBF). Project partners are the fact-checking organization CORRECTIV and research teams from Ruhr-Universität Bochum and TU Dortmund. Goal of the project is the creation of a crowd-working online platform for fact-checking.
A successful applicant is also expected to play an active role in the supervision of Bachelor's and Master's theses on topics of the research project. An extension of the position for another three years through a follow-up project in the thematic field of disinformation detection is being sought.
- A successfully completed university degree (Master, Diplom or equivalent) preferably in the area of electrical engineering, computer engineering, computer science, computational linguistics, or media technology
- Knowledge in several of the following areas:
- Natural language processing
- Machine learning, statistics, and information theory
- Image and/or video processing
- Excellent programming skills in Python, Matlab, Java, or C/C++
- Interest in solving challenging engineering problems
- Motivation to conduct independent scientific research
- Excellent communication skills in German and English (written and spoken)
How to apply:
Please send your application with the usual documents (in a PDF document, max. 5 MB) exclusively by e-mail to email@example.com
, quoting the reference number
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or quick access 214041.
To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities.
Technische Universität Berlin - Die Präsidentin - Fakultät IV, Institut für Energie- und Automatisierungstechnik, FG Elektronische Systeme der Medizintechnik, Prof. Dr. Kolossa, Sekr. EN 3, Einsteinufer 17, 10587 Berlin