1) Data Mining in Social Networks
2) Node Deletion and Edge Deletion Problems in Networks
More details about the projects, funding, expected skills and how to apply are provided below.
ABOUT THE PROJECTS
1) Data Mining in Social Networks: Social data from networks such as Twitter and Facebook can be represented as networks. Similarly, various data about city living obtained through City Observatory housed in the Technology & Innovation Centre (TIC) Future Cities theme can be represented in a similar structure, using individuals as nodes of such a network and their connections as edges of the network. The proposed project will design efficient algorithms to mine opinions and sentiments in such networks, in particular in real-time and when big data is present. The problem of sentiment and opinion analysis involves studying the negative and positive expressions opined in social media on a specific subject matter. We will work on such algorithms that volume and velocity of data accumulated in the context of social media is the most crucial design factor. This will also exploit some of the theoretical insights gained in an ongoing cross-faculty PhD project with Department of Mathematics & Statistics. The project aims to establish both theoretical and computational analysis, using various tools and techniques such as network optimization, design of algorithms and integer programming. As part of the computational work, we plan to use ARCHIE-WeSt, the high performance computing centre housed at University of Strathclyde.
2) Node Deletion and Edge Deletion Problems in Networks: In this project, we plan to develop efficient algorithms to study the node and edge deletion problems on networks. These problems stem from various important applications in energy networks (e.g., how to build a network that can survive failures on particular power lines), epidemic containment (e.g., how to ensure disconnectivity between various populations) and defense operations (e.g., where to focus attacks on enemy to ensure faster victory). The problem involves in effectively identifying a subset of nodes or edges of a network, which on deletion results in a subgraph with desirable properties. Some of the properties of interest include the connectivity in the graph, a restrictive size of the largest component, and denseness of the components formed. As part of the research, we plan to establish theoretical and empirical analysis for two specific network types. The theoretical work might include methods such as complexity analysis, analysis of the hardness of approximation and developing approximation algorithms and polyhedral analysis for the problems. The experimental work might involve designing and implementing exact computational integer programs and efficient heuristics that would be built upon the theoretical foundation.
FUNDING AND ELIGIBILITY
Funding is available to cover 3 years of tuition fees for a UK/EU/international student, plus a tax free stipend higher than £14,000 per year. The student will be given opportunities to attend a conference and/or specialized training every year.
These PhD projects require a highly numerate graduate with skills and interests in computational science. Candidates should have at least a strong Honours degree or equivalent (a strong 2:1 Honours degree, or a B.Sc. degree with 3.3 GPA in a 4.0 system), or preferably a Master's degree in a quantitative discipline such as industrial engineering, operations research, mathematics or computer science (amongst others). Experience in programming and fundamental knowledge in optimization (in particular integer programming) are not essential but highly desirable. Candidates who are not native English speakers will be required to provide evidence for their English skills (such as by IELTS or similar tests that are approved by UKVI, or a degree completed in an English speaking country)
Applications are admitted until 31st May, or until a suitable candidate is found thereafter.
HOW TO APPLY
All PhD applications are to be made online at http://pgr.strath.ac.uk/. All documents (including scans of original documents) can be uploaded during the online application process. Candidates are expected to submit a cover letter, a research proposal detailing their 3-year plan, CV, any university degree certificates and transcripts, English test results (if applicable), two recommendation letters (or contact details of two referees, if letters are not available to them), and any other supporting documents. In order to be considered for this studentship, candidates should specifically note the title of this project in their online application when prompted about funding and their source of finance, and they should notify Ms Alison Kerr for their intent for studentship application.
More information about the department can be found here: http://www.strath.ac.uk/business/managementscience/
Enquiries regarding applications to: Ms Alison Kerr (firstname.lastname@example.org)
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