Research Assistant - salary grade E13 TV-L Berliner Hochschulen

The Chair of Electronic Systems of Medical Engineering develops machine learning and signal processing methods for human-centered applications. Our work lies at the intersection of machine learning, statistics and neuroscience and focuses on speech and language processing in multi-modal settings.

Applications include, for instance, speech recognition for medical purposes, and machine learning methods for modeling human speech perception and for developing multimodal hearing support. We are looking for a scientific staff member for a three-year fully funded position in this area, in close collaboration with the Ben Gurion University, for a current research project with DFG funding. The successful candidate will design and scientifically evaluate generative and discriminative models for multi-channel audio-visual speech enhancement. The position is suitable for obtaining a PhD in electrical engineering or computer science.

We offer an inspiring, international, and interdisciplinary working environment at a young research institute in the heart of Berlin.

• Successfully completed university degree (Master, Diplom or equivalent) in Computer Engineering, Computer Science, or Electrical Engineering or a related field with outstanding results
• Excellent programming skills in Python, Java, or C/C++
• Demonstrated experience in machine learning for speech and video signals
• Good knowledge of German and/or English required; willingness to acquire the respective missing language skills
• Knowledge in several of the following areas:
• Generative models for speech and audio signals
• Signal processing for multi-channel audio data
• Fundamentals of auditory science and neurophysiology

We are looking for highly motivated, curious, and enthusiastic researchers with excellent academic achievements and a strong interest in the development of neurobiologically inspired machine learning methods for multi-modal hearing support.

Please send your application with the usual documents (in a PDF document, max. 5 MB) exclusively by e-mail to dorothea.kolossa@tu-berlin.de, quoting the reference number.

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guaranty for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/ 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. Applications from people of all nationalities and with a migration background are very welcome.

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