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<p class="MsoNormal" style="text-align:justify"><span lang="FR">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.<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="FR">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.
<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="FR">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.<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="FR"><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="FR">Applications will be collected through the UNIGE portal
<a href="https://www.iit.it/careers/openings/opening/1215-1-phd-position-in-bioengineering--bioelectronics-at-iit-in-collaboration-with-universit-di-genova">
https://www.iit.it/careers/openings/opening/1215-1-phd-position-in-bioengineering--bioelectronics-at-iit-in-collaboration-with-universit-di-genova</a>. Deadline for application is June 15th.
<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="FR">Please feel free to contact us for informal enquire.
<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="FR">Contacts: <a href="mailto:michela.chiappalone@iit.it">
<span lang="EN-US" style="color:windowtext;text-decoration:none">michela.chiappalone@iit.it</span></a>;
<a href="mailto:marianna.semprini@iit.it"><span lang="EN-US" style="color:windowtext;text-decoration:none">marianna.semprini@iit.it</span></a> <o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="FR"><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><span lang="FR"><o:p> </o:p></span></p>
<p class="MsoNormal" style="text-align:justify"><u><span lang="FR">References:<o:p></o:p></span></u></p>
<p class="MsoNormal" style="text-align:justify;text-indent:.5in"><span lang="FR">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.<o:p></o:p></span></p>
<p class="MsoNormal" style="text-align:justify;text-indent:.5in"><span lang="FR">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.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="FR"><o:p> </o:p></span></p>
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<p class="MsoNormal"><span lang="IT"><o:p> </o:p></span></p>
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