***** To join INSNA, visit http://www.insna.org ***** *Fully funded PhD studentship (4 years) in Aston University, UK* http://www.jobs.ac.uk/job/AXI678/phd-studentship-novel- paradigms-for-the-analysis-and-classification-of-non-vectorial-data/ Applications are invited to apply for a four year Postgraduate Research studentship, supported by the School of Engineering and Applied Science, to be undertaken within the Computer Science subject group at Aston University. The successful applicant will join the recently established System Analytics Research Institute (http://www.aston.ac.uk/eas/ research/groups/systems-analytics-research-institute/). This studentship is combined with a teaching assistant role. The successful candidate will be required to provide up to an average of 6 hours per week of teaching support for a distance learning programme; therefore the student must be capable of teaching on an undergraduate course in Software Engineering. Details of teaching responsibilities and a list of taught modules can be found here. The position is available to start in September 2017 (or later by agreement) *Financial Support*: This studentship includes a fee bursary to cover the Home/EU tuition fee rate plus a maintenance allowance of £15,000 in 2016/17. Applicants from outside the EU may apply for this studentship but will need to pay the difference between the ‘Home/EU’ and the ‘Overseas’ tuition fees, currently this is £11,729 for the 2016/17 academic year. As part of the application you will be required to confirm that you have applied for, or, secured this additional funding. *Background of the Project*: Graph-based representations have long been used as a powerful way to characterise a large number of systems that are best described in terms of their structure. However, the rich expressiveness of graphs usually comes at the cost of an increased difficulty in applying standard pattern recognition techniques and machine learning to them. The aim of this project is to investigate novel ways to probe and characterise the structure of graphs. For example, in recent years, classical and quantum walks have emerged as a powerful way to measure the structural similarity between graphs and to define novel vertex signatures. However other processes, such as quantum walks with decoherence, have received little or no attention, despite having a number of unique and interesting properties. Other open problems that could be the subject of this project are the ability to cope with increasingly large and diverse input graphs (time-varying, multi-layer, etc.), as well as investigating the privacy concerns emerging in the analysis of real-world networks. *Person Specification*: The successful applicant will have a strong undergraduate (first class or upper second class) and/or Master’s degree in computer science, engineering, mathematics, physics or a related discipline as well as excellent programming and analytical/mathematical skills. Applicants with expertise and research interests lying at the intersection of graph theory, pattern recognition, and physics are particularly welcome to apply. Applicants from non-English speaking countries will need to satisfy Aston’s English language entry requirements. Enquiries about this project contact Dr. Luca Rossi ( http://www.cs.aston.ac.uk/~rossil/ <http://www.cs.bham.ac.uk/~rossil/>) by email: [log in to unmask] The online application form, reference forms and details of entry requirements, including English language are available at http://www.aston.ac.uk/eas/research/prospective-research- students/how-to-apply/ *Applications should also be accompanied by a brief research proposal, and an explanation of how your knowledge and experience will benefit the project.* -- Luca Rossi Lecturer in Computer Science School of Engineering and Applied Science Aston University Web: http://www.cs.aston.ac.uk/~rossil/ <http://www.cs.bham.ac.uk/~rossil/> _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.