Industrial PhD – Improved Speech Communication Using Personalized Voice Models

This Industrial PhD position focuses on advancing speech communication through the development and application of personalized voice models. The role requires a strong foundation in speech processing, machine learning, and signal processing techniques, with an emphasis on tailoring voice models to individual users to enhance communication effectiveness. Candidates should possess a doctoral-level education, indicating deep theoretical knowledge and research experience in relevant fields such as computer science, electrical engineering, or linguistics. As an intern-level role with limited experience points, the position is suitable for early-career researchers or doctoral candidates seeking to apply their academic expertise in an industrial context. Key competencies include proficiency in programming languages commonly used in speech and machine learning research (such as Python, MATLAB, or C++), familiarity with neural network architectures for voice modeling, and experience with data collection and analysis related to speech signals. Strong analytical skills and the ability to conduct rigorous experiments to validate personalized voice models are essential. The role also demands collaboration with interdisciplinary teams, combining insights from acoustics, human-computer interaction, and artificial intelligence to improve speech communication technologies. Overall, this position offers an opportunity to contribute to cutting-edge research aimed at enhancing user-centric speech applications through innovative personalized voice solutions.