The 'Signal Processing and Machine Learning' Group at the Institute of Communications Technology has an immediate vacancy in the area of speech and audio processing.
The tasks of a jobholder consist in performing scientific work in the area of speech and audio processing, in particular:
- Development of systems for noise reduction and acoustic echo cancellation using deep neural networks.
- Development of systems for automatic speech recognition using end-to-end deep neural network approaches
- Development of systems for reading-learning support using deep neural networks
- Development of systems for acoustic event classification using anomaly detection or few-shot learning methods
Your profile:
- Completed scientific university studies, especially in the field(s) of computer science, information technology, electrical engineering, applied mathematics.
- Very good English and German language skills, both written and spoken
- Very good knowledge in machine learning, experience with training frameworks (e.g. Tensorflow, PyTorch)
- Knowledge in speech signal processing is advantageous
- Fascination and engagement in machine learning!
What we offer:
- We offer you the opportunity for scientific qualification with the goal of a PhD.
- Depending on the topic and time, you will be hired as a scholarship holder or with remuneration according to EG 13 TV-L.
- Limited contract for 2 years with a possible prolongation up to 6 years
TU Braunschweig seeks to reduce underrepresentation in the sense of the NGG in all areas and positions. Therefore, applications from women are highly welcome. Candidates with disabilities will be preferred if equally qualified (in that case, please attach proof of disability). The application of people from all nations are welcome.
Please note that application costs cannot be refunded. Please note that personal data will be stored for the purpose of the application process.
Please send your application by email to Prof. Fingscheidt (t.fingscheidt(at)tu-bs.de), keyword 'SPEECH'.
Please summarize the usual documents (cover letter, certificates, curriculum vitae, etc.) in a pdf-file and state your interest in and suitability for at least one of the four topics mentioned above.
Technical University of Braunschweig
Institute for Communications Technology
Prof. Tim Fingscheidt
Schleinitzstrasse 22
38106 Braunschweig