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Deep Learning algorithms, reasoning and interpretation

School of Science

This project is no longer listed on and may not be available.

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Dr G Cosma No more applications being accepted Self-Funded PhD Students Only

About the Project

Deep learning is a subset of machine learning in artificial intelligence (AI) that is capable of learning from data.

Deep learning is receiving a lot of attention due to its ability to achieve unprecedented levels of performance in terms of accuracy and speed, to the point where deep learning algorithms can outperform humans at decision making, and tasks such as classifying images, and real-time detection.

The emphasis of this project is the design and development of artificial intelligence algorithms which can provide reasoning behind predictions and decisions. Applications where reasoning is particularly needed include biomedical and healthcare predictive modelling applications.

Feature selection using Deep Learning has not been well studied, despite its importance which facilitates understanding of data and reasoning with machine learning outputs.

Projects under this topic may also concern the development of algorithms which are capable of removing irrelevant features from large uni-modal and multi-modal datasets with a view on providing reasoning behind predictions.

If you are interested please get in touch with Dr Cosma ([Email Address Removed]) to discuss the topic further.

You can find out more here:
How to apply
All applications are made online, please select the school/department name under the programme name section and include the quote reference number.
Entry Requirements
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Computer Science with a strong interest in data-science. Applicants must be competent in programming and applied mathematics, and should have a strong ability to write computer programs preferably in the Python programming language.

Funding Notes

This is an open call for candidates who are sponsored or who have their own funding. If you do not have funding, you may still apply, however Institutional funding is not guaranteed. Outstanding candidates (UK/EU/International) without funding will be considered for funding opportunities which may become available in the School.

UK/EU Fee band: Research Band 2 Laboratory Based (£TBC)
International Fee band: Research Band 2 Laboratory Based (£22,350)

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