Job Description

1) Project: This job opening covers a research position in the STADIUS group for a Ph.D. candidate in the frame of a project on signal processing for EEG and brain-computer interfaces. The Ph.D. candidate will focus on spatial filtering methods for neural interfaces, in particular for artifact removal and extraction of neural responses in high-density EEG systems. Part of the project also involves multi-modal signal processing combining audio recordings and neural (EEG) signal responses. A specific focus is on the design of adaptive and computationally-efficient neural signal processing algorithms, possibly in a real-time context and amenable to low-power distributed or parallellizable architectures (such as sensor networks or multi-core processors).

2) Profile: Candidates must hold a Masters degree in Electrical Engineering (or equivalent) with excellent grades, and with a strong background in (multi-channel) signal processing theory. Additional research/educational experience in spatial filtering,(blind) source separation methods, component analysis, audio and speech signal processing, sensor array processing, distributed signal processing, tensor methods, and/or machine learning are a strong plus. Excellent proficiency in the English language is also required,as well as good communication skills, both spoken and written.

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