MSC Thesis project wireless imaging device

We have an open position for an MSC student interested in the development of state-of-the-art wireless devices for simultaneously recording animal communication signals and brain activity. Our group has been developing sensors for recording vocal communication in songbirds (Anisimov at al., 2014) and wireless devices suitable for both recording and manipulation of behavior (Magno et al 2019).
We now want to further develop wireless sensor devices to enable applications in neuroscience research. We are a multidisciplinary research group working on elucidating the brain mechanisms underlying vocal learning by using small songbirds as a model species. Unlike rodents and non-human primates, who are limited to innate vocalizations, songbirds share with humans the ability to modify and learn vocalizations by imitating conspecifics. This vocal imitation ability relies on self-reinforced, auditory-guided motor learning. Many parallels between speech acquisition in humans and birdsong learning are present at the behavioral, neural, and genetic levels.
The MSC student will be mainly involved in the development of hardware/software solutions for remote sensing applications, in the design and fabrication of wireless Bluetooth low-energy devices for in vivo fluorescence recording of neuronal activity. The ideal candidate for this position has a solid background in engineering and/or neuroscience. A strong commitment to teamwork is a top asset and crucial for succeeding in this project.

Keywords: embedded devices, Bluetooth Low Energy, Arm Cortex, data compression, neural networks, fiber photometry, optogenetics.

V. N. Anisimov, J.A. Herbst, A.N. Abramchuk, A.V. Latanov, R.H.R. Hahnloser, A.L. Vyssotski. Reconstruction of vocal interactions in a group of small songbirds. Nature Methods 11, 1135–1137 doi:10.1038/nmeth.3114 (2014).
M. Magno, F. Vultier, B. Szebedy, H. Yamahachi, R.H.R. Hahnloser, L. Benini. A Bluetooth-Low-Energy Sensor Node for Acoustic Monitoring of Small Birds. IEEE Sensors Journal (2019).


Anja Zai (zaia (at)

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