Meet over 65 universities on 27 & 28 April GET YOUR FREE TICKET >
University of Portsmouth Featured PhD Programmes
Anglia Ruskin University ARU Featured PhD Programmes

Deep Reinforcement Learning for Smart Steel Processing


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

Click here to search for PhD studentship opportunities
Prof C Davis , Prof G Montana Applications accepted all year round

About the Project

Sequential decision making describes a situation where the decision maker makes successive observations of a process before a final decision is made. With recent advanced in artificial intelligence, and especially “deep learning” (artificial neural networks), much progress has been made in developing computer agents that are able to make sequential decision on their own. In this PhD project we will develop advanced artificial intelligence algorithms for sequential decision making for applications in smart steel processing.

The PhD project is part of SUSTAIN, an EPSRC-funded programme co-created by the 5 major UK steel producers (Tata, Liberty, British Steel, Celsa, Sheffield Forgemasters) and the three principal Universities that have expertise in this area (Swansea, Warwick and Sheffield) to provide academic leadership in the field of steel innovation. Although the steel industry has generated “big data” for over 30 years, the production benefits have been limited so far. In this PhD project, we will develop novel data-driven techniques that leverage the latest advances in data science and machine learning. Ultimately, we will deliver an AI system for Smart Steel Processing able to automate and optimise certain processes that still rely heavily on manual intervention. We will exploit existing historical data repositories made available by our industrial collaboration and the availability of next-generation sensors that are now replacing traditional sampling methods in extreme environments. We will also develop a “digital twin”, a simulation-based environment to help us test and develop novel reinforcement learning algorithms.


A minimum 2.1 undergraduate (BEng, MEng, BSc) and/or postgraduate masters’ qualification (MSc) in science and technology field: Computer Science, Engineering, Mathematics, ideally with specialisation in Machine Learning and AI. Familiarity with machine learning and probabilistic models is ideal.

Funding Notes

Funding of £18,009 per annum is available for UK/EU applicants for 3 years.

To be eligible for this project the successful applicant should have indefinite leave to remain in the UK and have been ordinarily resident here for 3 years prior to the project start-date, apart from occasional or temporary absences. Additional details of these criteria are available on the EPSRC website.

If you would like to be considered for this position or have any questions please complete our online enquiry form using the "Visit website" button below.

Search Suggestions

Search Suggestions

Based on your current searches we recommend the following search filters.

FindAPhD. Copyright 2005-2021
All rights reserved.