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We have 86 Machine Learning PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships in London



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

We have 86 Machine Learning PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships in London

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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Funded PhD Studentship on Robust and Efficient Machine Learning Algorithms

Overview. I am looking for a PhD student with an interest in the design of efficient and robust machine learning and data processing algorithms using tools from applied probability, signal processing and statistical mechanics. Read more

Engineering Networked Machine Learning via Meta-Free Energy Minimisation

Inspired by neuroscience, informed by information-theoretic principles, and motivated by modern wireless systems architectures integrating artificial intelligence (AI) and communications, this project sets out to develop a paradigm-shifting framework for networked machine learning (ML) that is centred on the following ideas. Read more

Machine Learning and Domain Decomposition methods for Fluid Dynamics

Modelling of many modern applications leads to linear systems whose size is too large to allow the use of direct solvers. Thus, parallel solvers are becoming increasingly important in scientific computing. Read more

Machine learning approaches in health data science for risk prediction of cardiovascular diseases

Cardiovascular disease is killing over 17 million people in the world. almost a third of the death from cardiovascular diseases occur suddenly without prior signs and symptoms or diagnosis of any heart conditions. Prediction and prevention of cardiovascular diseases are then a priority to prevent these deaths. Read more

Fully funded PhD scholarship in Optical Networks for Machine Learning Systems

Duration of study: Full time – 3.5 years fixed term. Starting date: Flexible, to start by September 2023. Application deadline: No closing date, the position will remain open until a suitable candidate is found. Read more

Design of digital technology and machine learning solutions for mental health

The significant societal and economic impact of mental health conditions worldwide is well documented. With a growing awareness of mental health, the pressing need to streamline access to sustainable care services is now an imperative. Read more

Generative Deep Learning Models for Automated Craniofacial Surgical Planning

Aims of the Project. Implement a deep learning-based approach to detect and localise craniofacial anomalies in children. Develop a generative method to simulate a stereotypical paediatric skull from a skull with detected anomalies using a skull atlas as reference. Read more

Physically-informed learning-based beamforming for multi-transducer ultrasound imaging

Aim of the PhD Project. Pursue sparse solutions to handle the channel count required to coherently operate multiple ultrasound transducer and design and implement machine learning strategies to avoid the sparsity-related artefacts in the images. Read more

Image-based Recognition of Unidentified Featured Objects (UFOs)

With the development of deep learning approaches and convolutional neural networks (CNN) in particular, the task of recognising objects from an image has become associated with the ability to train a network using a large number of labelled images for each class of interest [He2016]. Read more

Security and Privacy of Energy-Constraint Internet of Things Communication using Distributed AI

In recent years, the Internet of Things (IoT) has progressed dramatically due to advancements in technology. It plays an important role in the development of abundant applications and economic ventures. Read more

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