PhD Scholarship in Acoustic Signal Processing

Job summary

This position involves developing innovative, energy-efficient methods for processing real-world acoustic signals, focusing on neuromorphic computation applications in acoustics. The role includes contributions to next-generation acoustic sensing systems through various advanced techniques.

Qualifications

• A two-year master's degree (120 ECTS points) or equivalent academic level.
• Strong foundations in signal processing and applied mathematics.
• Background in acoustics or acoustic signal processing (e.g., array processing, source localization).
• Experience with machine learning models (e.g., PyTorch/Jax) and familiarity with spiking-network frameworks is advantageous.
• Fluent in English, with excellent communication skills.

Responsibilities

• Develop brain-inspired computational methods for acoustic sensing and inference.
• Work on continuous-time and sparse representations of acoustic fields.
• Design auditory front-ends inspired by biological systems.
• Realize hardware solutions for low-power acoustic sensing.
• Address challenges in acoustic perception and scene analysis.

Skills

• Strong analytical and problem-solving skills.
• Ability to collaborate with diverse teams and backgrounds.
• Interest in interdisciplinary work at the intersection of acoustics and machine learning.

Education

• A master's degree in a relevant field is required.

Tools

• Familiarity with programming languages and frameworks related to machine learning and neuromorphic hardware.