[visionlist] Postdoc position in: Biological neural-network signal encoding using Artificial Intelligence
enver.sangineto at unitn.it
Fri Sep 6 09:40:38 -04 2019
Postdoc position in: Biological neural-network signal encoding using
Location: University of Trento, Italy
Duration: One year (it may be renewed for a second year).
Applications are invited for one full-time postdoctoral research
position funded by the Brandy project
(https://projects.unitn.it/brandy/) and in collaboration with the ERC
project Backup (https://r1.unitn.it/back-up/). The goal of both projects
is to investigate the brain network functioning using an
inter-disciplinary approach. We are currently seeking a highly motivated
Postdoc with a strong research record in Artificial Intelligence areas
such as: Audio Processing, Signal Processing, Speech Recognition,
Computer Vision, etc.
The successful candidate will participate in proposing, implementing and
applying Deep Learning methods for the analysis and the interpretation
of electrophysiological signals of biological neuronal networks.
Specifically, we will use a Multi-Electrode Array (MEA) to access the
activity of a culture of in-vitro alive neurons. The MEA response is a
set of time-varying signals, one signal per electrode, usually
characterized by a very low Signal-to-Noise-Ratio (SNR). These raw
signals (possibly pre-processed to increase the SNR) will be used to
train an artificial neural network in order to predict (“encode”) the
biological neuron activity in the near future. Predicting the future
activity of the biological neurons will show that the artificial network
can “understand” and internally represent the “semantics” of the input
MEA signal. We will investigate Deep Learning methods for brain
(neuronal network) activity encoding and we will generalize the proposed
methodology to different kinds of brain activity signals (e.g., fMRI,
The successful candidate will work in the NL lab of the Physics
department of the University of Trento, supervised by Dr. Enver
Sangineto and in collaboration with both the Artificial Intelligence
group of Prof. Nicu Sebe (http://mhug.disi.unitn.it/ ) and the
Nanoscience Laboratory of Prof. Lorenzo Pavesi
(http://nanolab.physics.unitn.it/), in a strongly inter-disciplinary
group composed of Computer Scientists, Biologists and Physicists.
For more information, please contact Dr. Enver Sangineto
(enver.sangineto at unitn.it).
Interested applicants should send:
1. a one-page cover letter summarizing their interests, how they can
contribute to the project, as well as the earliest date that they can
start the appointment,
2. curriculum vitae, and
3. contact information for two references
to: enver.sangineto at unitn.it. Only applicants considered for employment
will be contacted. Applications are reviewed on a rolling basis.
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