[Neuroinfo] Fully funded PhD position on computational methods for brain connectivity analysis

[Diego Sona]

We are seeking candidates for a PhD position entitled “Computational Methods for Brain Connectivity Analysis” which mainly concerns with the development of novel approaches (based on pattern recognition and machine learning methodologies) for the brain connectivity analysis of neuroimaging data (fMRI, rsMRI, DTI, MEG, EEG, etc.).

The PhD grant is jointly supported by Fondazione Bruno Kessler (FBK) and Istituto Italiano di Tecnologia (IIT). The research activity will take place at the Neuroinformatics Laboratory (NILab, https://nilab.fbk.eu/ <https://nilab.fbk.eu/>) and the Pattern Analysis and Computer Vision Department (PAVIS, http://pavis.iit.it/ <http://pavis.iit.it/>). NILab is an interdisciplinary laboratory raised as joint initiative between the Centre for Information Technology of FBK and the Centre for Mind/Brain Sciences of University of Trento (CIMeC, http://www.cimec.unitn.it <http://cimec.unitn.it/>).

The applicant should have a strong background in machine learning and pattern recognition methodologies with a keen interest in neuroscience. The successful candidate will have the opportunity to work in an interdisciplinary environment.

Interested candidates are invited to contact Paolo Avesani (avesani at fbk.eu <mailto:avesani at fbk.eu>) and Diego Sona (diego.sona at iit.it <mailto:diego.sona at iit.it>) by emailing their CV and a short statement of interest in this position.

The candidates must in any case formally apply for the PhD grant following the instructions in the call published by Università degli studi di Trento (see the application webpage http://ict.unitn.it/application/ict_doctoral_school <http://ict.unitn.it/application/ict_doctoral_school>) referring to position A3.

Deadline for formal application is May 31, 2017, hrs. 04.00 PM (Italian time, GMT +2)

For further information on the position and the application process refers to the following links
http://ict.unitn.it <http://ict.unitn.it/application/ict_doctoral_school>
http://ict.unitn.it/application/project_specific_grants <http://ict.unitn.it/application/project_specific_grants>


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