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Computer Science & IT (repair) PhD Projects, Programs & Scholarships

We have 5 Computer Science & IT (repair) PhD Projects, Programs & Scholarships

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  Digitisation of Technical and Smart training programmes to deliver a market leading on-line solution to maximise efficiency to global markets.
  Prof A Hossain
Application Deadline: 23 July 2019

Funding Type

PhD Type

PhD Fully-Funded Studentship. Studentship code IIIP0006. School of Computing and Digital Technologies. Teesside University and TTE Technology Institute.
  Distributed implementations of machine-learnt defect detection for Additive Manufacturing (EPSRC CDT in Distributed Algorithms)
  Dr P Green, Dr X Guo
Application Deadline: 31 August 2019

Funding Type

PhD Type

Additive Manufacturing (AM) is revolutionising UK industry. It is a tool-less digital approach that produces highly customised parts on demand, anywhere in the product life cycle (from prototyping to maintenance and repair) (Gupta, Weber, & Newsome, 2012).
  Integrative Computational Biology and Machine Learning: Combining computational biology, computational chemistry, and machine learning techniques with biological big data to unravel the higher genomic code of life
  Dr A Sahakyan, Prof P McHugh
Application Deadline: 26 July 2019

Funding Type

PhD Type

In the Sahakyan Group, we strive to make computational biology maximally independent from empirical experimental data, by basing our models and predictions on genomic sequences and core biological mechanisms.
  Using Artificial Intelligence to Study Variations in Gas Turbine Performance
  Research Group: Computational Engineering and Design
  Dr D Toal, Prof A Keane
Application Deadline: 31 August 2019

Funding Type

PhD Type

Artificial Intelligence (AI) allows the rapid processing of images. In the context of gas turbines this means that scans and video imaging of engine parts could be automatically assessed for variations in shape that can have significant impact of fuel consumption and engine life.
  Machine Learning for classifying and characterising living cell cultures
  Research Group: Intelligent Systems and Nanoscience
  Prof S Smith
Applications accepted all year round

Funding Type

PhD Type

In collaboration with the Department of Biology at the University of York and the Department of Computer Science at the University of Sheffield, programmable agent-based computational models have been developed to help interpret how populations of cells arise and repair from individual cell:cell interactions.
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