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Statistics PhD Projects, Programs & Scholarships in Manchester

We have 35 Statistics PhD Projects, Programs & Scholarships in Manchester

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  Ensuring efficient, equitable and sustainable support for people with care needs in ageing societies
  Dr Marcello Morciano, Prof M Sutton
Application Deadline: 14 June 2020

Funding Type

PhD Type

The PhD will be undertaken within the Economic Sustainability research theme of the National Institute for Health Research Applied Research Collaboration for Greater Manchester (ARC-GM).
  The Manchester Dementia Prediction Database: Using advanced statistical methods to optimise diagnosis and prognosis for people with degenerative neurological conditions.
  Dr J Thompson, Dr A Woollams, Dr M Jones
Applications accepted all year round

Funding Type

PhD Type

Early diagnosis and accurate prognostic information are key priorities to enable people with neurodegenerative dementia to know what to expect and to enable them to plan effectively for their future needs.
  Characterising B cells in Rheumatoid Arthritis: Their role in susceptibility, pathogenesis, and treatment response
  Dr S Viatte, Dr D Plant, Dr Q-J Meng, Prof A Barton
Applications accepted all year round

Funding Type

PhD Type

Note. Dr D Plant is the main supervisor for this project. Background. Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease that primarily affects the joints.
  Applying radiomics to improve outcomes in cervix cancer
  Dr A Green, Dr A McWilliam
Applications accepted all year round

Funding Type

PhD Type

Cervix cancer is a growing problem in worldwide. Thanks for continuous improvements in cancer treatments, such as radiotherapy, many women survive their disease but they can also experience side effects from their treatments.
  CFD and inverse UQ for investigation of drop/bubble dynamics
  Prof K Law, Dr A Thompson, Dr C Pena-Monferrer
Applications accepted all year round

Funding Type

PhD Type

Applications are invited for a PhD position in the Department of Mathematics at University of Manchester funded by EPSRC Industrial CASE and IBM Research UK.
  Bayesian statistical approaches to identification of shared genetic signals
  Dr H Guo, Prof C Berzuini
Applications accepted all year round

Funding Type

PhD Type

Project description. A number of genes have been found associated with health conditions of interest (e.g. autoimmune disease) from multiple studies.
  Developing a sizing methodology for women’s sports compression garments
  Dr K Brubacher, Dr S Gill
Application Deadline: 30 June 2020

Funding Type

PhD Type

SCGs are skin-tight, elastic garments that are designed to apply pressure to the underlying body with the aim to improve exercise performance, shorten recovery and prevent injuries.
  Improved classification of myositis disease subtypes using statistical genetics approaches for stratified medicine
  Dr J Lamb, Dr AM Morris, Dr H Chinoy
Applications accepted all year round

Funding Type

PhD Type

Keywords. idiopathic inflammatory myopathy, myositis, genetics, disease classification, stratified medicine. Idiopathic inflammatory myopathies (IIM) are heterogeneous autoimmune diseases characterized by inflammation of skeletal muscle (myositis).
  Effective models for function-structure relationship in complex biological media
  Dr I Chernyaysky, Prof O Jensen
Applications accepted all year round

Funding Type

PhD Type

A complex multiscale relationship between the structure and function is common in many human organs (such as the lung, liver and placenta), and many diseases are associated with an imbalance in the relationship.
  An investigation of psychological and clinical factors associated with the development of chronic or persistent pain in children and young people with inflammatory and non-inflammatory musculoskeletal conditions.
  Dr L Cordingley, Prof W Thomson, Dr R Lee, Dr J McDonagh
Applications accepted all year round

Funding Type

PhD Type

Background. Juvenile Idiopathic Arthritis (JIA) is an inflammatory arthritis presenting in children and young people. Pain is one of the main features of JIA and it is often described as one of the most burdensome yet invisible symptoms of this long-term condition.
  Advancing Methodology for Clinical Prediction
  Dr M Sperrin, Dr G P Martin
Applications accepted all year round

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].
  Social Statistics PhD opportunities

Funding Type

PhD Type

Change lives and shape futures with a PhD in Social Statistics. Join a vibrant. postgraduate research community. that includes students from all over the world.
  Integrative statistical inference methods for eukaryotic gene regulation with applications to embryonic stem cell differentiation
  Dr I Iqbal, Prof M Rattray, Prof A Sharrocks
Applications accepted all year round

Funding Type

PhD Type

Embryonic stem cells (ESCs) can differentiate into different cell types through intermediary cell states and deeper understanding of the regulatory control underlying these differentiation stages is a very important topic in the study of mammalian development (Yang et al., 2014 & 2019).
  Development of image analysis methods and software to study musculoskeletal diseases using artificial intelligence (AI)
  Dr Claudia Lindner, Prof T Cootes
Applications accepted all year round

Funding Type

PhD Type

Musculoskeletal (MSK) diseases affect an increasing number of the population globally. In the UK, on average 3 in 10 people are affected, which increases to 1 in 2 in the age group 65+.
  Development of Convolutional Neural Networks and Associated Error Estimation Techniques for Vertebral Segmentation in Axial Computed Tomography Image Slices
  Dr N Thacker, Dr P Bromiley
Applications accepted all year round

Funding Type

PhD Type

Osteoporosis is a common skeletal disorder that increases the risk of fractures and causes significant morbidity and mortality. Vertebral fractures (VFs) are often an early manifestation of osteoporosis but are significantly under-diagnosed in clinical practice.
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