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Medical / Clinical Science (analytics) PhD Projects, Programs & Scholarships

We have 5 Medical / Clinical Science (analytics) PhD Projects, Programs & Scholarships

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  Predictive analytics to facilitate shared decision making in advanced cancers: The importance of communicating risk to advanced cancer patients
  Dr A Hopkins, Prof MJ Sorich
Applications accepted all year round

Funding Type

PhD Type

Project Title. Predictive analytics to facilitate shared decision making in advanced cancers. The importance of communicating risk to advanced cancer patients.
  Pharmacoepidemiological study to systematically investigate drug-related adverse events in older people
  Dr P Nishtala
Applications accepted all year round

Funding Type

PhD Type

A self-funded PhD studentship is available under the supervision of Dr Prasad Nishtala at the University of Bath. This is a collaborative project which will involve working with Dr Hamish Jamieson from the Big Data and Ageing Research Group at Christchurch, NZ.
  A novel approach to the development of an antimuscarinic potency tool and measuring anticholinergic burden in older people
  Dr P Nishtala
Applications accepted all year round

Funding Type

PhD Type

A self-funded PhD studentship is available under the supervision of Dr Prasad Nishtala at the University of Bath. This is a collaborative project which will involve working with Dr Hamish Jamieson from the Big Data and Ageing Research Group at Christchurch.
  Examining the longitudinal associations of polypharmacy and frailty with functional decline in older people with multimorbidity
  Dr P Nishtala
Applications accepted all year round

Funding Type

PhD Type

A self-funded PhD studentship is available under the supervision of Dr Prasad Nishtala at the University of Bath. This is a collaborative project, which will involve working with Dr Hamish Jamieson from the Big Data and Ageing Research Group at Christchurch and Dr Danijela Gnjidic at the University of Sydney.
  Machine learning and multi-level GLM models as alternatives to logistic regression in propensity score estimation for the study of medical devices using observational data
  Prof D Prieto-Alhambra, Dr V Strauss, Dr S Khalid
Application Deadline: 16 August 2019

Funding Type

PhD Type

Observational studies of medical devices may provide evidence on comparative safety in real life patients. Regulatory bodies including the FDA have showed interest in the use of evidence from studies using routinely collected data.
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