Decarbonisation of Oil and Gas Production Platforms: AI Prediction for Integrated Energy Systems

About the Project

Project Title: Decarbonisation of Oil and Gas Production Platforms: AI Prediction for Integrated Energy Systems

Robert Gordon University, through the School of Computing, Engineering and Technology, is offering a PhD studentship in Integrated Energy Systems and AI.

Currently, oil and gas platforms rely heavily on fossil fuels for power generation, significantly contributing to global CO₂ emissions. As the transition to develop renewable energy resources continues, there is a need to balance the provision of stable energy supplies from the offshore oil and gas energy sector whilst reducing emissions. This research aims to support this decarbonisation strategy – reducing CO₂ emissions of offshore oil and gas platforms using a hybrid of renewable energy sources and integrating advanced artificial intelligence (AI) models.

The objective is to develop a bespoke AI model, that will predict, manage and monitor energy requirements and associated emission profile. This approach helps balance the intermittent nature of renewable energy sources with changing energy demands of offshore platforms.

Using AI to manage energy and emissions will help offshore platforms move towards a Net Zero energy system, aligning with global goals to reduce carbon emissions. This project has the potential to lower the carbon footprint of offshore operations, facilitating the Energy Transition by improving energy efficiency and ensuring a more sustainable and environmentally friendly energy supply for the future.

Background: introduction to the research area/topic with intext referencing

Rationale: clear discussion of justification of the project and the knowledge gap it is intended to address with intext referencing

Aim: statement of the overall intended outcome of the research work

Objectives: not more than 5 SMART bullet point objectives)

Literature Review: 2-3 pages with intext referencing

Methodology: how each stated objective will be achieved

List of References: as cited intext

Applications should be emailed to Dr Ibiye Iyalla at i.iyalla1@rgu.ac.uk. The application should consist of a covering letter or personal statement of interest, and a CV.

Deadline for receipt of applications is 30 June 2026.

It is expected that candidates are available to register and commence study no later than October 2026.

Questions should initially be address to:

Dr Ibiye Iyalla

School of Computing, Engineering and Technology

Robert Gordon University

Sir Ian Wood Building, Garthdee Campus

Aberdeen, AB10 7GJ

United Kingdom

T: +44 (0) 1224 262386

E: i.iyalla1@rgu.ac.uk

Entry Requirements

Applicants should have (or be expected to achieve) an MSc, or a First- or Second-Class UK honours degree (or equivalent) in a relevant discipline such as Engineering and Computing. Knowledge and experience of Renewable Energy, Machine Learning and AI application will be advantageous though not required.

Applicants must:

• Be home, RUK or EU fee status
• Have not already obtained a PhD.
• Be studying full time and on campus

Applicants should also demonstrate:

• A suitable academic background.
• Enthusiasm, motivation and determination to succeed.
• A strong commitment to self-development and take a pro-active and committed approach to research
• Have an awareness of, and interest in, the energy sector.
• Possess good communication and interpersonal skills

Keywords: Decarbonisation, AI, Integrated Energy Systems, Offshore Production Platform

Funding Notes

This studentship will cover UK Home/EU tuition fees and provide a tax-free stipend for three years set at the standard UKRI rates. The stipend for academic year 2025/2026 is £21,805.