[Comp-neuro] PhD position at Rehab Technologies Lab (Italian Institute of Technology)
Marianna.Semprini at iit.it
Fri May 29 06:37:21 CEST 2020
We seek a highly motivate PhD student for working at the Rehab Technologies Lab at IIT.
Rehab Technologies is an innovation lab aimed at translating robotic technologies into hi-tech medical products for people with disabilities, including also neural interfaces and personalized neuroengineering solutions for promoting neuroplasticity, with the goal of replacing and/or retraining motor functionalities. We are also interested in monitoring the neural correlates of the rehabilitation treatment, by means of measures based on network connectivity extracted with hdEEG.
The PhD project will mainly focus on this activity and will thus include experiments with patients and strong collaboration and interaction with our clinical partners. To this end, the candidate will benefit from a lively network of collaborations with hospitals and research institutions in Italy and abroad.
The ideal candidate should: hold a degree in electronic/biomedical engineering or related disciplines, have proficient programming skills (Matlab/Simulink, C and/or Python), be a highly motivated and creative individual who wants to work in a dynamic, multi-disciplinary research environment. Former lab experience and previous technical and scientific results will be highly considered.
Applications will be collected through the UNIGE portal https://www.iit.it/careers/openings/opening/1215-1-phd-position-in-bioengineering--bioelectronics-at-iit-in-collaboration-with-universit-di-genova. Deadline for application is June 15th.
Please feel free to contact us for informal enquire.
Contacts: michela.chiappalone at iit.it<mailto:michela.chiappalone at iit.it>; marianna.semprini at iit.it<mailto:marianna.semprini at iit.it>
* Iandolo R., Semprini M., Buccelli S., Barban F.iit, Zhao M., Samogin J., Bonassi G., Avanzino L., Mantini D., Chiappalone M. (2020). Small-World Propensity Reveals the Frequency Specificity of Resting State Networks. IEEE Open Journal of Engineering in Medicine and Biology.
* Semprini M., Laffranchi M., Sanguineti V., Avanzino L., De Icco R., De Michieli L., & Chiappalone M. (2018). Technological approaches for neurorehabilitation: from robotic devices to brain stimulation and beyond. Frontiers in Neurology, 9, 212.
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