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University of Liverpool, School of Electrical Engineering, Electronics and Computer Science Computer Science & IT PhD Projects, Programs & Scholarships

We have 9 University of Liverpool, School of Electrical Engineering, Electronics and Computer Science Computer Science & IT PhD Projects, Programs & Scholarships

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Showing 1 to 9 of 9
  AI approaches for NMR analysis of biomolecular mixtures
  Dr A Lisitsa, Dr I Barsukov
Applications accepted all year round

Funding Type

PhD Type

This position will remain open until a suitable candidate has been found. This is an interdisciplinary project (Computer Science and Biochemistry) aimed at the development of novel AI methods for the analysis of Nuclear Magnetic Resonance spectra.
  An Intelligent Assistant for Medical Doctors when Prioritising Pathology Results
  Dr S Scanlon, Dr G Burnside
Application Deadline: 28 June 2019

Funding Type

PhD Type

The project is supported by the University of Liverpool Doctoral Network in Future Digital Health, which is directed at creating and maintaining a community of AI health care professionals that can realise the benefits that AI can bring to Health Care.
  An intelligent imaging technology for automatic characterisation of the refractive power of human eye
  Prof Y Shen, Dr Y Zheng
Application Deadline: 28 June 2019

Funding Type

PhD Type

The project is supported by the University of Liverpool Doctoral Network in Future Digital Health, which is directed at creating and maintaining a community of AI health care professionals that can realise the benefits that AI can bring to Health Care.
  Deep Feature Learning for Distributed Rehabilitation Robots with Wearable Tactile Sensing
  Dr S Luo, Dr P Paoletti
Application Deadline: 28 June 2019

Funding Type

PhD Type

The project is supported by the University of Liverpool Doctoral Network in Future Digital Health, which is directed at creating and maintaining a community of AI health care professionals that can realise the benefits that AI can bring to Health Care.
  Deep Learning with main target to Discover High-Temperature Superconductors (Ref: LRC1903CS)
  Dr JY Goulermas, Prof M J Rosseinsky, Dr M Gaultois, Dr V Gusev
Application Deadline: 31 July 2019

Funding Type

PhD Type

High temperature superconductivity has great promise to transform society because it offers the transmission of electricity without loss of energy and the creation of large magnetic fields with applications including healthcare.
  Deep Learning with main target to Discover Solid Electrolytes for New Battery Technology (Ref: LRC1905CS)
  Dr Y Goulermas, Prof M J Rosseinsky, Dr M Gaultois, Dr V Gusev
Application Deadline: 31 July 2019

Funding Type

PhD Type

In the quest towards safer and higher capacity batteries, the development of an all-solid-state battery is a top priority, and is currently limited by the lack of a high-performance material to serve as a solid state electrolyte.
  Designing efficient search strategies for new materials (Ref: LRC1907CS)
  Dr Y Goulermas, Prof M J Rosseinsky, Dr M Gaultois, Dr V Gusev
Application Deadline: 31 July 2019

Funding Type

PhD Type

This position will remain open until a suitable candidate has been found. Reference LRC1907CS. There is an urgent need to develop new experimental strategies to discover functional materials.
  Machine Learning of Epidemic Models
  Dr D Wojtczak
Application Deadline: 28 June 2019

Funding Type

PhD Type

The project is supported by the University of Liverpool Doctoral Network in Future Digital Health, which is directed at creating and maintaining a community of AI health care professionals that can realise the benefits that AI can bring to Health Care.
  Optimal search strategies for automated, robotic material discovery
  Dr J Fearnley, Prof A Cooper
Applications accepted all year round

Funding Type

PhD Type

This position will remain open until a suitable candidate has been found. New functional materials are central to society but they can be hard to find in the laboratory because of the astronomical search space that is defined by the available atomic and molecular building blocks.
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