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reconstruction PhD Projects, Programs & Scholarships

We have 74 reconstruction PhD Projects, Programs & Scholarships

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Showing 1 to 10 of 74
  Data-driven reconstruction algorithms for Magnetic Resonance Elastography
University of Nottingham School of Mathematical Sciences
  Dr M Iglesias, Prof D Avitabile, Dr D McGrath
Applications accepted all year round
Modelling and Analytics for Medicine and Life sciences Doctoral Training Centre. PhD Scholarship. Supervisors. Marco Iglesias (School of Mathematical Sciences), Daniele Avitabile (School of Mathematical Sciences) and Deirdre McGrath (School of Medicine).
Details
Type/Funding
  Long-term performance and sustainability of post-disaster housing projects (Advert Reference: RDF19/EE/ABE/WEDAWATTA)
Northumbria University Faculty of Engineering and Environment
  Dr G Wedawatta
Application Deadline: 25 January 2019
One of the four key priorities of the Sendai Framework of Action 2015-2030 (1) is to ‘Build Back Better’ in recovery, rehabilitation and reconstruction.
Details
Type/Funding
  Locally-adaptive Bayesian modelling for medical image reconstruction
University of Leeds School of Mathematics
  Dr R.G Aykroyd
Applications accepted all year round
The use of medical imaging techniques are critical in the early diagnosis and treatment of many serious conditions. Over the past 20-30 years there have been major advances in imaging speed and resolution along with equally dramatic decreases in cost.
Details
Type/Funding
  Large-scale Urban Reconstruction, Classification, and Rendering from Remote Sensor Imagery
Concordia University Computer Science and Software Engineering
  Prof C Poullis
Applications accepted all year round
This project addresses the current technological difficulties of rapid and automatic reconstruction of large scale areas and seeks solutions for the development of accurate, robust and scalable methods and systems for processing the big data captured by active and passive sensors in order to produce a realistic virtual representation.
Details
Type/Funding
  Multi-scale network reconstruction and modelling of phage – bacteria interactions
University of Manchester Faculty of Biology, Medicine and Health
  Dr J-M Schwartz, Prof S Lovell
Applications accepted all year round
Bacteriophages are viruses that infect bacteria. They are seen as a promising alternative to antibiotics, particularly as multi-resistant bacterial strains are becoming more widespread and could one day render existing antibiotic therapies ineffective.
Details
Type/Funding
  Photogrammetry for Fine-Scale 3D Model Acquisition
Manchester Metropolitan University Faculty of Science and Engineering
  Dr T Collins
Applications accepted all year round
Research Institute Reference Number. EMRC-TC-2018-1-PhD. Project Summary. The focus of this project is on the photogrammetric acquisition of 3D virtual objects.
Details
Type/Funding
  Machine learning aided engine exhaust tomographic imaging
University of Edinburgh School of Engineering
  Dr C Liu
Application Deadline: 31 December 2018
Aero gas turbine engines are meeting ever-increasingly stringent emission requirements on the concentrations of toxic compounds, minimising the adverse environmental effects of civil aviation activities.
Details
Type/Funding
  "Are we there yet?" Quantifying progress of invasive non-native species eradication using spatial capture-recapture and pedigree reconstruction.
Aberdeen University School of Biological Sciences
  Prof X Lambin
Applications accepted all year round
Invasive non-native species (INNS) threaten biodiversity world-wide. In Scotland, introduced mammals including American mink, hedgehogs, grey squirrels and stoats damage multiple SPA or SAC designated areas.
Details
Type/Funding
  Deformable 3D reconstruction of endoluminal anatomy by miniature steerable chip-on-tip endoscopy
King’s College London School of Biomedical Engineering & Imaging Sciences
  Dr C Bergeles
Applications accepted all year round
1st Supervisor - Dr Christos Bergeles. 2nd Supervisor - Professor Kawal Rhode. Chip-on-tip steerable endoscopes are rapidly improving due to tandem innovation in robotics technology and highly-integrated cameras.
Details
Type/Funding
  Field scale reconstruction of nineteenth century rural land use using first County Series OS maps and parish area books
Kingston University Faculty of Science, Engineering and Computing
  Prof N S Walford, Dr D Brown
Applications accepted all year round
The project will explore agricultural land use change in mid-nineteenth century England, which was a period of relatively high prosperity and stability before the onset of an era of decline and depression from the early 1870s through to the twentieth century.
Details
Type/Funding
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