[Comp-neuro] PhD Studentship available on Computational Intelligence for Artificial Agents Cognition and Interaction

Di Nuovo, Alessandro A.DiNuovo at shu.ac.uk
Mon Jan 11 14:35:31 CET 2016

Dear all,

This is to announce a PhD Studentship available on Computational Intelligence for Artificial Agents Cognition and Interaction 

The project explores the use of Computational Intelligence techniques to simulate the human-like cognition abilities and use them to address complex real-world problems in which artificial agents should autonomously learn and interact with human beings. In particular, it investigates the novel deep learning paradigm offers a highly biologically plausible way to train neural network architectures with many layers, inspired by the hierarchical organization of the human brain. Impressive results have been obtained in several areas, where deep learning architectures have outperformed state-of-the-art algorithms on various tasks, such as computer vision, automatic speech recognition, natural language processing, and human action recognition.
the position advertised within the SHU VC & ACES Graduate Teaching Assistant (GTA) PhD Scholarship Schemes 2016 (Project n. 6 in Computing and Informatics).

Deadline for the application is 29th of January 2016. 

Please follow the link below for more information. 


which has general information on  the types of scholarships available, eligibility criteria and profiles of 2015 VC scholars (the landing page can also be found by clicking on the featured link on the SHU website home page).  From the landing page, applicants can then click through to more detailed application information, according to discipline. 

Note that students are chosen in competition with students who choose projects in other fields, which means that we would particularly encourage strong applicants with very good academic marks and previous research experience to apply. 

All applicants are encouraged to contact a prospective supervisor before submitting an application.

If you are interested on the project, please contact the project lead: Dr Alessandro Di Nuovo (a.dinuovo at shu.ac.uk).

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