Modeling Non-Linearities in Digital Speaker Systems

1 month ago


Lund, Skåne, Sweden Axis Communications Full time
Job Description

We are seeking a highly motivated and skilled researcher to work on a Master Thesis project focused on modeling non-linearities in digital speaker systems. The goal of this project is to explore the possibilities of using machine learning algorithms, specifically deep learning and neural networks, to model these phenomena with high precision.

About the Project

The scope of this thesis project includes the exploration of different approaches to modeling non-linearities in digital speaker systems, as well as the evaluation of automated identification algorithms for these models. The project will also involve benchmarking the models using real digital speaker system measurements.

Requirements
  • A strong background in audio technology, engineering, machine learning, signal processing, or embedded firmware development
  • A Master's degree in a related field, such as Computer Science, Electronics Engineering, Acoustics Engineering, Mathematics, or Physical Sciences
  • An interest in exploring the possibilities of using machine learning algorithms to model non-linearities in digital speaker systems
Benefits

This project offers the opportunity to work on a cutting-edge topic in the field of audio technology and machine learning. As part of this project, you will have access to state-of-the-art facilities and expertise, and you will be able to contribute to the advancement of knowledge in this area.

Salary and Benefits

The estimated salary for this position is $65,000 - $80,000 per year, depending on qualifications and experience. In addition to the salary, you will receive a comprehensive benefits package, including health insurance, paid time off, and retirement savings plan.

How to Apply

If you are a motivated and skilled researcher with a strong background in audio technology, engineering, machine learning, signal processing, or embedded firmware development, we encourage you to apply for this position. Please submit your CV, cover letter, and university/college grade summary via the proposal advert. We look forward to hearing from you



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