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/Job opportunities/Neuromodulation through micro-electrodes with combined stimulation and recording capacity in a semi-flexible implantable format

Neuromodulation through micro-electrodes with combined stimulation and recording capacity in a semi-flexible implantable format

PhD - Leuven | More than two weeks ago

An active participation in the development of (medical) electronic devices for human implantation by optimization of electrode materials and their device integration technologies.

Implants in the human body are serving important applications in medicine already today: cochlear implants, deep brain stimulation devices and pain modulators are offering therapy to thousands of people.  But the technology used in those implants is still in its infancy and there is a lot of room for improvement. Microchip technology has the possibility to radically enhance and open new application avenues for implantables.  Current implants have only a few stimulation or recording channels, and hence there is no real feedback possible.  Imec’s neurotechnology platforms are using silicon-based integration schemes that can push the boundaries forward in terms of resolution for neuromodulation by using recording and adaptive stimulation schemes.  One of the major challenges is to develop new improved electrode materials that are CMOS compatible and sustain the high current densities required for stimulation.   Moreover, the whole microchip needs to be biocompatible and embedded in a biomimetic semi-flexible package.

In this PhD the candidate explores novel electrode materials and integration schemes to build better implants. He/she will develop and characterize novel electrode materials for their capability to efficiently record from and stimulate tissue (such as the brain). Further, integration of these devices onto heterogenous packaging solutions for long term implants will be explored as well.

Required background: Engineering technology, Engineering science, Biomedical engineering, Chemical engineering, or equivalent

Type of work: 60% experimental, 30% interpretation, 10% theory/ literature study

Supervisor: Liesbet Lagae
Co-supervisor: Dries Braeken/Maaike Op de Beeck

The reference code for this position is 2020-114. Mention this reference code in your application.

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