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We have 23 Statistics PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships in Manchester

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Mathematics

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Manchester  United Kingdom

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Statistics PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships in Manchester

We have 23 Statistics PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships in Manchester

A PhD in Statistics focuses on mastering the mathematical framework behind data analysis. You will be researching processes that help understand data and assess risks. Even though Statistics contains a major component of theoretical maths, it has plenty of application in other fields like Physics, Biology or Finance.

What’s it like to do a PhD in Statistics?

On a PhD level, you’ll be using your existing knowledge of the models and methods in Statistics to work on a unique project that offers significant contribution to the field. Statistics is a vast area of study and you can look at one of some of these popular research topics in Statistics:

  • Bayesian statistics
  • High dimensional data
  • Computation techniques
  • Extreme value theory
  • Probability theory
  • Wavelets

Statistics also has applications in other areas like Biology, Medicine, Finance or Physics. You can, therefore, also decide to focus on a particular application of Statistics. For example, you can have a special focus on statistics within biomedical or social science.

Akin to many other STEM subjects, Statistics PhDs are usually advertised with a research objective. You can also propose your own research projects and they might be considered if they meet the over-arching objectives of the department.

In the UK, a PhD will end with submitting a thesis of around 80,000 words followed by an oral examination where you will defend your research in front of an academic panel. It is also likely that you’ll be asked to enroll as an MPhil student at the beginning of your programme. You can upgrade to a PhD, after a review at the end of the first year, if your supervisor feels your work meets certain standards

Since a PhD is a purely research-based degree, there are no compulsory teaching hours. You’ll work on a mutually decided schedule with your supervisor. However, because of the transdisciplinary nature of the field of Statistics, you might be encouraged to take on some taught modules, that cover certain transferable skills, in your first year.

Entry requirements

If you’re looking to do a PhD in Statistics, you’ll need to have completed a Masters (with Merit or Distinction) in a mathematical subject. Some research programmes may also accept degrees in subjects like Physics, Engineering or Computer Science, provided they have a major mathematical component.

Depending on where you choose to apply, you may also need to show that you have a level of language proficiency in your university’s language of instruction

PhD in Statistics funding options

In the UK, the Engineering and Physical Sciences Research Council (EPSRC) funds PhDs in Statistics. They offer fully funded studentships and a monthly stipend to UK students. PhDs are usually advertised with the funding attached and you’re automatically eligible for it if you’re successful in your application.

If you are an international student, you have the option of the EPSRC PhD Scholarships that contribute towards your tuition fee but do not include a monthly stipend.

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PhD in Statistics careers

A PhD prepares you for a career in academia and the industry. Agriculture, forensics, finance and law are some of the biggest employers of Statistics graduates outside of academia. You can also look at careers in Actuarial Sciences after a PhD in Statistics.

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Clinical prediction modelling methods to improve accuracy through time and space

Clinical prediction models (CPMs) are tools that predict patient outcomes based upon their demographics and clinical risk factors and are used throughout healthcare to aid decision making and for monitoring, auditing and planning. Read more

Model of Energy Demand and Carbon Reduction for Control of Energy Storage

The techniques of Control Theory, Artificial Intelligence and Statistical Data Analysis have been applied to engineering systems with great success, and the resulting is better energy efficiency using storage. Read more

Enhanced variant interpretation for the discovery of mechanisms underpinning Ophthalmic genomic disorders

This project will utilize large genomic sequencing datasets from the 100,000 genomes project and the UK BioBank to understand how genomic variation impacts the development and function of cells vital for correct vision. Read more

Detecting subtle but clinically significant cognitive change in an ageing population

A major challenge facing dementia research is identifying the earliest indicators of clinically-significant cognitive decline. This research project will be linked to the newly established Memory Assessment & Cognitive Ageing Research Unit (MACARU), led by the primary supervisor. Read more

Development of deep learning methods and software to infer pathway enrichment from histology images - application to liver fibrosis

Histopathological images are routinely used to characterize complex phenotypes. For example, pathologists regularly study stained images of tissue biopsies for cancer diagnosis as cancer is known to change the morphological features of cells including cell shape and size [1]. Read more

Data Science for Multiscale Urban Climate Modelling and Projection

  Research Group: Atmospheric Science
Although just 1%–3% of the Earth's land surface is urbanized, more than half of the world's population lives in urban areas, and this proportion is expected to reach 70% by 2050. Read more

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