We have 122 Data Science PhD Projects, Programmes & Scholarships for UK Students



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Data Science PhD Projects, Programmes & Scholarships for UK Students

We have 122 Data Science PhD Projects, Programmes & Scholarships for UK Students

A PhD in Data Science will help you gain expertise in the areas of data collection, storage, cleaning and analysis. You can also focus on areas such as predictive modelling and collaboration with other fields to extract value from the data.

What's it like to do a PhD in Data Science?

Data Science is a field that is constantly evolving. The quantity of data produced every day is increasing and so is the need for professionals who can help make sense of it. A PhD in Data Science will help you do just that. You will be researching into a particular problem in Data Science or developing new techniques to handle data.

Some popular research topics in Data Science include:

  • Machine learning
  • Computer vision
  • Natural language processing
  • Text mining
  • Cyber security

Your research might involve writing a thesis or producing a portfolio of academic publications. You will be advised to read certain amount of material during your PhD. You will also be required to complete a compulsory research training module during your first year.

To be able to complete a PhD in Data Science, you will need to work under the guidance of a supervisor who will help you with your research and provide guidance on writing your thesis.

A PhD in Data Science takes between 3-4 years to complete. If you are doing a PhD that entails writing a thesis, you will also have to submit an 80,000-word thesis at the end of your programme.

Entry requirements

In most countries, entry requirements for a PhD in Data Science will involve having a Bachelors and a Masters degree in a related subject. You might also be asked to show proficiency in the language of instruction in your programme.

You might also need some professional experience in Data Science.

PhD in Data Science funding options

In the UK, a PhD in Data Science will most likely have funding attached to it. This means you could have a full tuition fee waiver and a monthly living cost stipend. If you are applying for a PhD that has funding attached, you will automatically be considered for funding if your application is successful.

PhD in Data Science careers

Data Science is a constantly growing field with a lot of opportunities in sectors such as finance, technology and medicine. You can also find opportunities in teaching and research. If you want to continue your career as a data scientist, you can find opportunities in sectors like business intelligence or predictive modelling.

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Learning a universal biomolecular force field

Molecular dynamics has been successful in obtaining biological insights by simulating the motion of biomolecules. Increases in compute power mean that simulations will soon reach the time scales on which much of biology happens. Read more

PhD Studentship in System Services in 100% Renewable Grids

Applications are invited for a PhD studentship, to be undertaken as part of the project “System Services in 100% Renewable Grids” at Imperial College London (Electrical and Electronic Engineering (EEE) Department). Read more

Economics and Computational Analysis of Causal Inference

This project aims to uncover the connections between economics and computational analysis in order to gain a deeper understanding of how things like economic policies and changes impact our lives. Read more

Soc-B Studentship: 4 Year PhD in Biosocial Research

The Soc-B Centre for Doctoral Training (CDT) offers unique PhD training in biosocial research funded by the Economic and Social Research Council (ESRC) and the Biotechnology & Biological Sciences Research Council (BBSRC) to build capacity in this growing area of interdisciplinary scientific endeavour. Read more

Automating knowledge synthesis in biomedical literature using AI and language models

Knowledge synthesis can be a slow and cumbersome process but is an essential tool for medical and public health policy-makers. Formal systematic reviews require rigid protocols and extensive human effort from trained professionals, whereas a massive volume of research evidence emerges every year. Read more

Exploring the value of using large third-party artificial intelligence models in epidemiology, with examples using Twitter data

Large language models (LLMs) are an artificial intelligence approach that have recently been shown to have extremely promising ability, for example, for conversing with humans or performing tasks such as summarising or extracting information from text. Read more

Trustworthiness of Cardiac digital twins

Aims of the Project. Cardiac digital twins combine AI approaches in physics/physiologically-constrained frameworks. To develop trustworthiness in digital twins we will test how to perform global sensitivity analysis on a virtual cohort. Read more

Optimizing Deep-Learning Solutions for Computational Imaging

The Statistics and Data Science group in the School of Mathematics, University of Birmingham, is recruiting a PhD student working on the cutting-edge data-driven algorithms for solving imaging inverse problems.  This research aims at improving the quality of imaging via advancing the state-of-the-art reconstruction algorithms. Read more

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