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Statistics (analytics) PhD Projects, Programs & Scholarships

We have 10 Statistics (analytics) PhD Projects, Programs & Scholarships

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  Data science frontier: theory and algorithm
  Prof L Cao
Applications accepted all year round

Funding Type

PhD Type

Theoretical breakthroughs in frontier data science will be built on top of statistic learning and deep learning for complex data analytics and learning.
  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.
  Robust analysis of multivariate extreme events
  Dr K Strokorb, Prof A Zhigljavsky
Applications accepted all year round

Funding Type

PhD Type

Being well-informed about the likely nature of future risks is of utmost importance to build a resilient infrastructure through adaptation.
  Transferability of genetic risk scores for complex human diseases across diverse population groups
  Dr AM Morris, Dr J Bowes
Applications accepted all year round

Funding Type

PhD Type

Genome-wide association studies (GWAS) have been extremely successful in identifying DNA variants that are associated with a wide range of complex human traits and common diseases.
  NERC GW4+ DTP PhD studentship: Linking large-scale oceanic and atmospheric forcings to local scale flooding via machine learning
  Dr T Kjeldsen
Application Deadline: 6 January 2020

Funding Type

PhD Type

This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP).
  Big data approach to systematically investigate adverse drug reactions in older people
  Dr P Nishtala
Application Deadline: 8 December 2019

Funding Type

PhD Type

The University of Bath is inviting applications for a PhD position under the supervision of Dr Prasad Nishtala https://researchportal.bath.ac.uk/en/persons/prasad-nishtala and Professor Neil McHugh https://researchportal.bath.ac.uk/en/persons/neil-mchugh.
  Rapid digitisation of early-stage prototypes and physical to digital synchronisation in product design
  Dr C Snider, Prof B Hicks
Applications accepted all year round

Funding Type

PhD Type

Summary. This project will investigate processes and technologies to capture the form and behaviour of physical prototypes and generate synchronised digital representations.
  Rapid hybrid manufacture of prototypes and digital to physical synchronisation in product design
  Dr C Snider, Prof B Hicks
Applications accepted all year round

Funding Type

PhD Type

Summary. This project will investigate methods and systems to rapidly generate and alter physical models to synchronise with digital versions.
  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).
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