[Infovis] Fully funded PhD studentship

Sara Johansson Fernstad sara.fernstad at northumbria.ac.uk
Wed Dec 23 09:47:32 CET 2015

Fully funded PhD Studentship in Big Data Analysis and Visualization

Applications are invited for a fully funded Computer Science PhD studentship at the University of Northumbria at Newcastle, UK, in the area of Big Data Analysis and Visualization (http://master.findaphd.com/search/ProjectDetails.aspx?PJID=61931, application deadline 15 Jan).

About the project
In this ‘Big Data’ era, the amount and complexity of data that are gathered are constantly increasing. The challenge of today lies in analysing and generating knowledge from it. Information Visualization and Data Mining utilize and develop computational and interactive visual methods to support understanding of patterns and gaining of insights from such data. It acts as a link between data and the human interpreter, and has become crucial for gaining insights from data. ‘Big Data’ challenges are relevant in a range of scientific and industrial domains. For example, biosciences and biomedicine are areas that in recent years have become increasingly data driven, with a growing interest in development of efficient visualization methods and analysis tools.

Building on the supervisory team’s previous work in multivariate data visualization, data mining, biological visualization and bioinformatics, and guided by the interests of the candidate, this project will address some of the main challenges in biological data analysis, which will also be applicable in a range of other domains.

Potential subjects of focus include:
1) Interactive analysis of very high dimensional data – developing techniques that address challenges arising with data sets including tens or hundreds of thousands of dimensions
2) Integrative analysis of heterogeneous data – developing techniques that address challenges in joint analysis of data of several types and from several sources
3) Visual analysis of uncertain and missing data – developing techniques for analysis of data quality
4) Visual analysis of complex networks, such as biological pathways – developing techniques that facilitate overview and interpretability of networks and interrelated data

Within the project the candidate will design and implement interactive visualization methods. The project is thus suitable for a candidate with computer science background and, preferably, experience of visualization, data mining and/or HCI.

Further details about the project, supervisory team and application process can be found at http://master.findaphd.com/search/ProjectDetails.aspx?PJID=61931

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