[Comp-neuro] Fully funded PhD position at the IIT - neural coding - open now
stefano.panzeri at gmail.com
Mon Dec 16 18:28:37 CET 2019
Fully funded PhD Position at IIT - Computational approaches to study the
neural code for somatosensation.
I am are seeking candidates for a fully funded PhD position at the Italian
Institute of Technology’s in my lab (
https://www.iit.it/people/stefano-panzeri ). IIT collaborates with SISSA
and finances the positions at the PhD course at SISSA from the EU Marie
Curie Training Network Neutouch (www.neutouch.eu).
Although formally to be enrolled at SISSA, the successful candidate will
conduct research in my laboratory at the IIT headquarters in Genova, Italy.
The PhD project can focus on any of the research topics about somatosensory
neural information processing that are of interest to the candidate, to my
lab and to the Training Network (www.neutouch.eu), including: developing
mathematical analysis methods and neural network models for studying neural
population coding of somatosensory signals, for studying the neural bases
of sensory perception and decision making, and for designing somatosensory
neuro-inspired artificial sensors.
The ideal candidate should have a strong background in numerate sciences,
and have a strong propensity for interdisciplinary research. No extensive
previous experience in neuroscience is required. However, a keen interest
in understanding the brain is essential.
The position is open immediately and will close when a suitable candidate
is found. Interested candidates are invited to contact me informally by
email (stefano.panzeri at iit.it) as soon as possible, by attaching their CV
and briefly explaining their interest in this position, to initiate
discussions about potential PhD projects of interest.
For recent representative publications from my lab, please see:
van Vugt B, et al, (2018) *Science* 360, 537-542
Zaldivar, D., et al, (2018) *Current Biology* 28: 224-235
Runyan C. A., et al (2017) *Nature*: 548: 92-96
Pica G. et al, *NIPS* (2017)
Panzeri, S, et al (2017) *Neuron* 93: 491-507
Safaai, H. et al (2015) *Proc. Natl. Acad. Sci. USA* 112(41): 12834–12839
Fasoli, D. et al (2016) *PLoS Computational Biology*, 12(8): e1004992.
Panzeri, S., et al (2015) *Trends in Cognitive Sciences* 19: 162-172
Einevoll, G., et al (2013) *Nature Reviews Neuroscience*, 14, 770-785
stefano.panzeri at iit.it
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