Artificial Intelligent (AI) for Characterisation of Hydrogen (H2) Blend Fuels Combustion

University of Kent
June 25, 2023
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Scholarship value

The scholarship includes home/overseas tuition fees plus a combined maintenance grant and salary equivalent to the Research Councils UK National Minimum Doctoral Stipend (£18,662 for 2023/24) for the first three years followed by fees and a maintenance grant for a further six months. Scholars also receive fee-paid teacher in Higher Education training through the Associate Fellowship Scheme.


Sunday 25 June 2023, 23:59 BST


We are looking for an enthusiastic self-motivated candidate who can demonstrate academic excellence, outstanding research potential and ability to teach. Applicants with a relevant first degree and strong master’s degree in Engineering, Computer Science, or areas relevant to the PhD topic, and ideally, be familiar with artificial intelligence, image processing and data- driven are encouraged to apply.

Further details

We are recruiting for a fully funded PhD Studentship which will be awarded as a Graduate Teaching Assistant (GTA) to work with Dr Moinul Hossain on a research project titled “Artificial Intelligent (AI) for Characterisation of Hydrogen (H2) Blend Fuels Combustion” in the School of Engineering at the University of Kent. Combustion characteristics of H2 blend fuels are substantially different from those of natural gas such as methane, extensive studies are needed to better understand the complex combustion characteristics of a mixture of natural gas and H2. Recently, AI has shown success in characterising the combustion process. However, major hurdles faced are the selection of accurate input variables and feature extraction for efficient performance. Also, existing machine learning-based models only offer point prediction value, however, there are uncertainties associated with point prediction. This project aims to develop an advanced AI-enabled model to characterise the combustion states of H2 blend fuels. The model will be established using the reconstructed flame images and other sensor data. Training and testing datasets will be created to train and validate the model. The established model will be tested for different blend fuels and conditions. A data analytics tool will be developed based on the correlation of flame data and the blend conditions for evaluating the current state of the combustion process, and the impact of fuel blends on the safe and reliable operation of the applications.

Alongside completing your PhD programme of research and development, as a GTA you will normally be expected to work for 200 hours per annum in years 1 to 3, including teaching (maximum 96 contact hours per year) or demonstrating (maximum 130 contact hours per year) and related duties such as marking, preparation and examination. Further details of GTA terms and conditions are here:

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The University of Kent is committed to equality, diversity, widening participation and inclusion and we endeavour to recruit students from all walks of life. We encourage enquiries and applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status

How to apply

Apply for an Electronic Engineering PhD at IPP login screen ( and specify the research topic “Artificial Intelligent (AI) for Characterisation of Hydrogen (H2) Blend Fuels Combustion”.

Enquiries should be directed to Moinul Hossain ([email protected]), or the Admissions team [email protected].

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