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personalised medicine PhD Projects, Programs & Scholarships

We have 23 personalised medicine PhD Projects, Programs & Scholarships

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  Personalised Medicine for Breast and Ovarian Cancer
  Dr N Buckley, Dr H McCarthy
Applications accepted all year round

Funding Type

PhD Type

One in two people will develop cancer in their lifetime and it is a leading cause of death. While significant progress has been made in the treatment of some cancers, there still remain some forms of the disease with limited treatment options and poor outcome.
  A personalised medicine approach to the treatment of low dose interleukin-2 in amyotrophic lateral sclerosis: predicting patients’ response through blood transcriptomics
  Dr J Kirby, Dr D Wang
Application Deadline: 29 January 2020

Funding Type

PhD Type

Background. The Horizon 2020 funded project, MIROCALS, is a clinical trial of low-dose interleukin-2 (IL-2) in patients with amyotrophic lateral sclerosis (ALS), an adult onset neurodegenerative disorder.
  Mathematical and statistical evaluation of Positron Emission Tomography (PET) data for the management of cancer
  Dr M Nath, Prof A Welch, Dr F McKiddie
Application Deadline: 13 March 2020

Funding Type

PhD Type

Combining advanced imaging technologies with patient-level characteristics, it is now feasible to diagnose, monitor and evaluate the prognosis of cancer patients and adopt appropriate treatment strategies tailored to individual patient leading to the concept of personalised medicine.
  Precision Medicine DTP - An integrated computational-experimental approach to identify and optimise combination drug therapy for non-alcoholic fatty liver disease (NAFLD)
  Research Group: Centre for Inflammation Research
  Prof J Fallowfield, Dr F Menolascina, Prof J Plevris
Application Deadline: 8 April 2020

Funding Type

PhD Type

Background. Non-alcoholic fatty liver disease (NAFLD) is the commonest cause of chronic liver disease (CLD), affecting 1 in 4 people worldwide.
  MyFemur: Multiscale modelling from clinical image to personalised model to manufacture (EPS2020/30)
  Dr U Wolfram
Application Deadline: 28 February 2020

Funding Type

PhD Type

Our vision in this project is to create a computational framework for the proximal femur that can allow clinicians to take limited clinical imaging data, e.g.
  Identifying biomarkers that may affect diabetes comorbidity
  Dr S Watterson, Dr P McClean
Application Deadline: 7 February 2020

Funding Type

PhD Type

It is estimated that 415 million people worldwide suffer from diabetes which will rise to 642 million by 2040 [1]. Ninety percent of cases are type 2 diabetes (T2D).
  Do the health benefits of exercise depend on medication status in type 2 diabetes?
  Prof M Davies, Dr T Yates
Application Deadline: 28 February 2020

Funding Type

PhD Type

The vast majority of those with type 2 diabetes mellitus (T2DM) are prescribed glucose lowering therapies to help manage their condition, with many taking multiple types of therapies concurrently.
  Bioinformatics studies of protein structures, functions and their interactions
  Dr L J McGuffin
Applications accepted all year round

Funding Type

PhD Type

The computational study of protein structures, functions and their interactions is fundamental to our understanding of disease.
  Predicting treatment response in juvenile idiopathic arthritis using a single cell genomics based approach
  Prof W Thomson, Dr S Smith, Mr P Martin, Prof A Morris
Applications accepted all year round

Funding Type

PhD Type

Background. Juvenile idiopathic arthritis (JIA) is a group of chronic arthropathies of unknown cause which can result in long-term disability and poor quality of life for children and can continue well into adult life.
  Network Inference and Machine Learning: Identification of Diseases-gene Regulation
  Dr F He
Application Deadline: 31 January 2020

Funding Type

PhD Type

Coventry University is inviting applications from suitably-qualified graduates for a fully-funded PhD studentship. The successful candidate will join the project ‘Network inference and machine learning.
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