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We have 492 Machine Learning PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships

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Machine Learning PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships

We have 492 Machine Learning PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships

A PhD in Machine Learning focuses on the application of mathematical and statistical models to find patterns in data. You'll be asked to identify, model, and evaluate the systems that can be used to improve the performance of computer systems.

What's it like to do a PhD in Machine Learning?

Traditionally, Machine Learning is divided into different subfields. You'll have the option of choosing from popular fields of study such as Computer Vision and Language Processing.

Some popular Machine Learning subfields are:

Computer Vision

You can opt for a PhD in Computer Vision if you're interested in developing computer systems that can analyse and interpret digital images and video. You'll likely be asked to research methods to improve object classification, image registration, object tracking, and object recognition.

Language Processing

If you're interested in a PhD in Language Processing, you'll be looking at ways to improve the way computers interpret, process, and generate language. You'll be researching methods and techniques to process, store, and search large text collections. You may also be asked to research methods to improve natural language processing.

Machine Learning also has application in other fields such as finance, healthcare, manufacturing, and retail. However, the above are the most popular areas of research.

A PhD in Machine Learning will require you to come up with a research proposal to be defended in an oral exam during your viva. Your research will involve experimentation and observation that may culminate in a publishable paper at the end of your project.

PhD in Machine Learning entry requirements

A PhD in Machine Learning requires a minimum of a 2:1 undergraduate degree in a related subject. You may also be asked to show that you have the necessary pre-entry experience in computer science.

PhD in Machine Learning funding options

A PhD in Machine Learning will most likely have funding attached, meaning if you're awarded a studentship, your tuition fees will be covered and you'll receive a monthly stipend.

PhD in Machine Learning careers

Machine Learning models form the basis of many technologies we interact with every day. A PhD in Machine Learning will equip you with the skills to enter a wide range of careers in industries such as finance, healthcare, retail, and defence. You may also choose to continue your research and aim for a career in academia.

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Using Cryptosporidium genomics for investigating outbreaks and disease transmission

In this exciting project the PhD student will identify outbreaks of cryptosporidiosis, with a supervisory team that includes clinical scientists from Public Health Wales and academics specialising in genomic and bioinformatics technologies. Read more

Improved Detection of Bovine Tuberculosis Infected Cattle using Artificial Intelligence

Bovine tuberculosis (BTB), caused by M. bovis, is the current biggest zoonotic disease problem in farms in the UK. The control and eradication of BTB hinges on prompt identification and removal of all infected cattle from the herd to prevent transmission to other animals as well as humans. Read more

Context Aware AI Techniques for Secure and Tamper-proof Satellite Image Distribution

This project is part of the . Centre for Doctoral Training in Geospatial Systems. . The successful candidate will be co-supervised by academics from within the School of Computing at Newcastle University, the School of Geography at the University of Nottingham and work alongside our external partner. Read more

Human and Computer Representation of Images Synthesised by Generative Adversarial Networks

Generative adversarial networks (GANs) are a family of cutting-edge Machine Learning techniques that allow users to generate large numbers of images (or other real-world data such as language, sounds, etc.). Read more

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