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/Job opportunities/Spatiotemporal profiling of neural circuits by single cell integrative analysis using High-Density MEA chips

Spatiotemporal profiling of neural circuits by single cell integrative analysis using High-Density MEA chips

PhD - Leuven | More than two weeks ago

Push the boundaries of investigating cellular networks at single cell level using integrative analysis techniques powered by imec's high-density MEA platform

Studying cellular networks such as neural circuits on a single cell level is essential in understanding complex disorders such as neurodegenerative diseases. Since the dawn of next-generation sequencing technologies and the power of stem cell engineering, it is now feasible to reveal the transcriptomic profile of thousands of cells from patients with poorly understood conditions. On the other hand, neural circuits, even in (simplified) cultured conditions, demonstrate convoluted and ultrafast communications. High-density electrode arrays and extensive data processing are being used to identify disease phenotypes from these in vitro circuits. Yet, a combination of transcriptomics and electrophysiology on the single cell level has not been achieved to date.


Imec's high-density microelectrode array (HD-MEA) platform is a powerful instrument to study cellular networks at single cell resolution. With more than 16k electrodes and an electrode pitch of 15um, the nanochip enables to study cellular processes at unprecedented level. It features several modalities such as electrical stimulation, electroporation, electrophysiological recording, and impedance spectroscopy to study a variety of cell types and assays. This system will be used to develop a completely new type of integrative single cell analysis method based on electroporation and multiplexed barcoding.


The successful student will learn how to work with the HD-MEA and develop novel assays to unravel neural circuits on a single cell level. Microfluidic integration for barcode delivery will also be included. The student will handle stem cell cultures and analyze electrophysiology and transcriptomics data and will work in close collaboration with researchers investigating disease models of neurodegeneration.

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

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

Supervisor: Liesbet Lagae

Daily advisor: Dries Braeken, Maarten Fauvart

The reference code for this position is 2021-085. Mention this reference code on your application form.

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