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University of Reading Data Analysis PhD Projects

We have 32 University of Reading Data Analysis PhD Projects

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  A new approach to modelling complex human/robot movement dynamics using techniques from machine learning
  Prof X Hong, Prof W Harwin, Prof R Mitchell
Applications accepted all year round

Funding Type

PhD Type

Advances in sensing and communications have made it easy to obtain large sets of measurements about an entity, activity or event.
  Big Data Analytics and Mining: investigating and testing distributed formulations of data mining algorithms that are suitable for the MapReduce paradigm and for other distributed computing approaches
  Dr G DiFatta
Applications accepted all year round

Funding Type

PhD Type

Big Data indicates very large and complex data sets that are difficult to process using traditional and sequential data processing applications.
  Big Data Mining for Fighting Dementia
  Dr G DiFatta
Applications accepted all year round

Funding Type

PhD Type

Dementia describes a set of symptoms that can include memory loss and difficulties with thinking, problem-solving or language. Alzheimer’s Disease (AD) is the most common cause of dementia and is a terminal neurodegenerative disease.
  Computer Vision and Remote Sensing – Terrain Feature Classifications
  Dr H Wei, Prof J Ferryman, Prof X Hong, Dr G DiFatta
Applications accepted all year round

Funding Type

PhD Type

The research is mainly concerned with automated image understanding and processing of remotely. sensed data, such as multispectral/hyperspectral images, as well as LIDAR data, which provide height information of terrain.
  Data Mining and Visualisation in High Dimensional Spaces
  Dr G DiFatta
Applications accepted all year round

Funding Type

PhD Type

The mining and the visualisation of data in high dimensional feature spaces require the design of efficient algorithms. In high dimensional data spaces distance functions lose their usefulness and optimisation techniques, machine learning and data mining algorithms are very inefficient and ineffective.
  Developing methods for the analysis of chromosome conformation data
  Dr T Thorne
Applications accepted all year round

Funding Type

PhD Type

Chromosome conformational data allows us to investigate the three dimensional structure of the genome. This project will involve developing novel computational and statistical methods for the analysis of genomic contact data.
  Developing pipelines for the inference of gene regulatory networks
  Dr T Thorne
Applications accepted all year round

Funding Type

PhD Type

Gene regulatory networks are fundamental to many processes that take place in the cell. However learning the structure of these networks from high-throughput experimental data and deriving useful biological insights is challenging.
  Development of a Visual Analtyics Methodology for Streaming Data
  Dr F Stahl
Applications accepted all year round

Funding Type

PhD Type

The velocity aspect of Big Data Analytics stems from recent advances in hardware and software technology to sense, capture process and communicate data.
  Development of Scalable Analytics Methods for real-time Data Streams
  Dr F Stahl
Applications accepted all year round

Funding Type

PhD Type

"Recent advances in data acquisition and processing hardware stress state-of-the-art data processing hardware. This project is developing new computationally mechanisms for the analytics of real-time streaming data for applications such as.
  Identification of tree species based on UAV captured images
  Dr H Wei, Prof J Ferryman, Dr F Stahl, Dr G DiFatta
Applications accepted all year round

Funding Type

PhD Type

Computer Computer vision technology has been found to be an important application in remotely sensed data understanding. This research exploits high‐resolution images captured by UAV payload cameras to identify tree species.
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