Funding

Competition funded (UK/EU and international students)

Project code

SENE8730124

Department

School of Energy and Electronic Engineering

Start dates

April 2024

Application deadline

19 January 2024

Applications are invited for a fully-funded three year PhD to commence in April 2024. 

The PhD will be based in the Schools of Energy and Electronic Engineering and Mechanical and Design Engineering, and will be supervised by Dr John Chiverton, Dr Aikaterina Karali and Dr. Andrea Bucchi.

Successful applicants will receive a bursary to cover tuition fees for three years and a stipend in line with the UKRI rate (£18,622 for 2023/24). Bursary recipients will also receive a £1,500 p.a. for project costs/consumables. 

 

The work on this project could involve:

  • Algorithmic development of techniques used for the simulation of 3D and 4D imaging data;
  • Training and development of generative neural networks;
  • Simulation and mathematical modelling of biological tissues;
  • Software programming using one or more of C++, Python or Matlab.

 

This project is a combination of two important and topical fields of research: the exciting world of deep learning based generative neural networks and the simulation of biological materials; specifically the structure and function of cells in their surrounding fibre based cellular matrix structures. New techniques will be created that bridge these interdisciplinary boundaries. 

Mathematical models and code will be developed and used to digitally synthesize, at high resolution, 4D synthetic imaging data. The image degradation process for a number of imaging modalities, such as nano-scale  X-ray Computed Tomography (XCT) will also be taken into account. Generative deep learning based techniques will be developed in tandem with conventional volumetric image processing techniques.

The work will build on existing techniques in the area of volumetric (3D) image simulation but also techniques based on deep learning for image processing [Chiverton et al]. Co-supervisory expertise will include the areas of bioengineering and microscopic imaging [Karali et al]. This could involve the development of a digital test-bed for the investigation of the role of the surrounding cellular matrix and the effect of its properties on the growth and proliferation of cells as well as the associated algorithmic and model developments. 

 

Entry requirements

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

Basic knowledge of at least one programming language and an engineering or science based degree is expected.

 

 

 

How to apply

We’d encourage you to contact Dr John P Chiverton  (john.chiverton@port.ac.uk) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, you can use our online application form. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.  Our ‘How to Apply’ page offers further guidance on the PhD application process.

If you want to be considered for this funded PhD opportunity you must quote project code SENE8730124 when applying.