This job is about developing practical filtering approaches by applying DSP and machine learning to denoise time series data, with non-Gaussian noise.
You can use any tools you are familiar with (Matlab, R, Mathematica), but our algorithms are ultimately written in Python, so part of the job is being able to describe the approach to a developer in the team.
You will need to have demonstrated extensive experience in DSP and filtering and be able to adapt your approaches to the problem. Experience in combining DSP with machine learning approaches such as neural networks is highly regarded. As a person, you will be a self starter, resilient and results-focused.
We are only interested in those who are serious about working on this job. If you can't commit time to the job, then don't apply. We will need you to complete a non-disclosure agreement to work on this job.
Please include the keyword "Decibel" at the top of your application. This allows us to reject spam applications.