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Data Analysis PhD Projects, Programs & Scholarships in Manchester

We have 91 Data Analysis PhD Projects, Programs & Scholarships in Manchester

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  (MRC DTP) Can we use techniques such as machine learning to improve the risk prediction of infection-related complications in order to optimise antibiotic prescribing?
  Prof T Van Staa, Dr V Palin, Dr D Wong
Application Deadline: 15 November 2019

Funding Type

PhD Type

Antimicrobial resistance is a major public health concern and overuse of antibiotics is a major factor in its development. One strategic aim of the Government’s approach to minimise this is to conserve and steward the effectiveness of existing treatments by optimising antibiotic prescribing practices.
  (MRC DTP) Closed loop brain-computer interfaces for neuromodulation in chronic pain
  Dr A Casson, Dr Manoj Sivan, Prof A Jones
Application Deadline: 15 November 2019

Funding Type

PhD Type

Chronic pain is a major public health concern. Around 28 million people in the UK live with chronic pain and the healthcare costs exceed those of heart disease, cancer or diabetes.
  (MRC DTP) Mental health and social care integration for patients with complex needs: how to inform equitable and efficient funding to local organizations
  Dr Laura Anselmi, Dr Marcello Morciano, Prof M Sutton, Prof P Bower
Application Deadline: 15 November 2019

Funding Type

PhD Type

Mental illness has been recognised as of equal importance to other forms of illness (so-called ‘parity of esteem’), but in spite of commitments to strengthen care provision, gaps in funding and care provision still exist.
  (MRC DTP) Statistical machine learning approaches cross-cohort multi-omics data
  Prof M Rattray, Dr C Yau
Application Deadline: 15 November 2019

Funding Type

PhD Type

Multimorbidity refers to the co-existence of two or more chronic conditions in an individual and its prevalence is increasing due to aging populations.
  (MRC DTP) Harnessing digital patient-generated health data to improve clinical decisions in people with long-term conditions
  Dr S Van der Veer, Dr Alan Davies, Prof JA Ainsworth
Application Deadline: 15 November 2019

Funding Type

PhD Type

One in four people in the UK live with one or more long-term conditions.
  (MRC DTP) Incorporating causal inference in clinical prediction models
  Dr M Sperrin, Dr G P Martin, Dr H Guo
Application Deadline: 15 November 2019

Funding Type

PhD Type

Clinical prediction models (CPMs) take what we know about a person and predict the probability of subsequent outcomes using a regression model or algorithm [1].
  (MRC DTP) Development of a software system to automatically detect and quantify foot collapse
  Dr Claudia Lindner, Prof T Cootes
Application Deadline: 15 November 2019

Funding Type

PhD Type

Charcot arthropathy is collapse of a joint secondary to peripheral neuropathy, most commonly secondary to diabetes or alcoholism.
  (MRC DTP) Improved identification of brain tumour extent on advanced multi-modality medical images
  Dr R Hinz, Dr David Coope, Dr M Asselin, Prof A Jackson
Application Deadline: 15 November 2019

Funding Type

PhD Type

Gliomas are primary brain tumours which span a spectrum from comparatively slow growing tumours in young adults to highly aggressive tumours presenting later in life.
  (MRC DTP) Understanding the mechanisms responsible for aberrant atrial calcium handling in heart failure
  Dr K Dibb, Prof A Trafford, Dr C Pinali
Application Deadline: 15 November 2019

Funding Type

PhD Type

Atrial fibrillation (AF) is the most common cardiac arrhythmia, expected to affect ~18 million Europeans by 2060. AF often occurs in patients with heart failure (HF), increasing their risk of death by ~2 fold.
  (MRC DTP) Computer-aided Detection of Osteoporotic Vertebral Fractures in Clinical Images Using Convolutional Neural Network Constrained Local Models (CNN-CLMs)
  Dr P Bromiley, Prof T Cootes, Dr EP Kariki
Application Deadline: 15 November 2019

Funding Type

PhD Type

Osteoporosis is a common, degenerative skeletal disorder that increases the risk of fractures and causes significant morbidity and mortality.
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