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Statistics (applied statistics) PhD Projects, Programs & Scholarships

We have 40 Statistics (applied statistics) PhD Projects, Programs & Scholarships

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  Big Data driven treatments for Pulmonary Fibrosis
  Prof Gisli Jenkins
Applications accepted all year round

Funding Type

PhD Type

We invite applications for a 3-year PhD position, funded by the University of Nottingham to study ‘Big Data driven treatments for Pulmonary Fibrosis’.
  Longitudinal trajectories of renal function, and dynamic prediction of progression to end-stage renal disease: a data-driven analysis and validation using regression and machine learning methods in a bi-national population-based cohort #NDORMS-2020/1
  Prof D Prieto-Alhambra, Dr V Strauss, Dr S Khalid, Dr D Robinson
Application Deadline: 10 January 2020

Funding Type

PhD Type

1. Prof Daniel Prieto-Alhambra. 2. Dr V Strauss. 3. Dr Sara Khalid. 4. Dr Danielle Robinson. 5. Dr Laurie Tomlinson. There is a scarcity of data on the natural history of chronic kidney disease (CKD) in the general population, and on markers of rapid progression to end-stage renal disease (ESRD).
  Strategies of handling missing data in federated data network #NDORMS 2020/9
  Prof D Prieto-Alhambra, Dr V Strauss, Dr A Delmestri, Prof I Petersen
Application Deadline: 10 January 2020

Funding Type

PhD Type

The use of electronic healthcare data is increasingly being proposed as a source of evidence to support drug development and regulatory decision making but also to understand the pathogenesis of diseases.
  Statistical Data Analysis of medical health records
  Prof B Schelter, Prof M Thiel
Applications accepted all year round

Funding Type

PhD Type

In this project we will use advanced statistical and mathematical modelling techniques to analyse patient health records in order to support medical decision making.
  ONE Planet DTP - Integrated modelling to predict early signs of land degradation (OP20297)
  Dr M Montero-Calasanz
Application Deadline: 31 January 2020

Funding Type

PhD Type

2.2 million tonnes of topsoil is eroded annually in the UK and over 17% of arable land show signs of degradation (Fig.1). Reversing soil degradation and restoring fertility by 2030 is an aim of the government’s 25 Year Environment Plan but there are insufficient data on the health of UK soils.
  Improving UK air quality forecasts during heatwaves
  Dr R Hossaini, Prof J Wild
Application Deadline: 17 January 2020

Funding Type

PhD Type

Poor air quality is a major global health concern affecting all industrialised nations and virtually all of society. Worldwide, ~3 million deaths are attributable to air pollution annually (World Health Organization), with ~40,000 premature deaths in the UK alone (Royal College of Physicians).
  Modelling the impact of interventions in atrial fibrillation, the commonest cardiac rhythm disorder and a global healthcare problem
  Dr G Czanner, Dr I Olier, Prof P Lisboa, Prof G Lip
Applications accepted all year round

Funding Type

PhD Type

Project description. It is known that the risk of developing CVD is increasing in the UK along with the rest of the World. It is believed that the culprits are lifestyle and environmental factors.
  Statistical and machine learning methods for risk prediction of cardiovascular diseases from complex longitudinal data
  Dr G Czanner, Dr I Olier, Prof P Lisboa, Prof G Lip
Applications accepted all year round

Funding Type

PhD Type

Project description. Risk prediction models are used in clinical decision making and are used to help patients make an informed choice about their treatment.
  Bayesian Uncertainty Quantification for Clustering Problems
  Research Group: Statistics
  Dr W Yoo, Dr S Liverani
Applications accepted all year round

Funding Type

PhD Type

The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing either in September 2020 for students seeking funding, or in January 2020 or April 2020 for self-funded students.
  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).
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