PhD scholarship in Acoustic Signal Processing - DTU Electro
On-siteKongens Lyngby, Capital Region, Denmark
Job Summary
Develop event-driven, energy-efficient methods for processing real-world acoustic signals by combining spiking neural networks, event-driven sensing, and classical acoustic signal processing. Push boundaries in continuous-time representations, auditory front-ends, hardware realization on neuromorphic platforms, and acoustic scene analysis under strict power and latency constraints. Collaborate on brain-inspired computational methods to open new approaches to acoustic sensing and inference. Contribute to the Danish Ph.D. program through coursework, teaching, and supervision of students while pursuing an external research stay.
Required Qualifications
- Solid foundations in signal processing and applied mathematics
- Some background in acoustics and/or acoustic signal processing (e. g. array processing, time-frequency analysis, source localization, room or underwater acoustics)
- You must be fluent in English, both speaking and writing and possess excellent communication skills
- You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree
Desired Qualifications
- Experience programming machine learning models (e. g. PyTorch/Jax)
- Familiarity with spiking-network frameworks (e. g. snnTorch or Norse)
- Experience with neuromorphic hardware
- An active interest in interdisciplinary work at the intersection of acoustics, machine learning, and neuromorphic engineering
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