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  Large Language models for Maintenance Optimisation


   School of Physics, Engineering and Technology

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

The University of York is embarking on transformative research in data-centric engineering, digital twins, and AI, revolutionizing the way systems are designed and operated. As part of this initiative, we are seeking applications for PhD positions in the field of Autonomous Intelligent Transportation Systems and Data Science.

This doctoral research project focuses on the optimization of maintenance practices using advanced large language models. By harnessing the power of emerging data science techniques, our goal is to enhance future maintenance operations in industries such as aerospace, automotive, energy, and railway.

In recent years, large language models like GPT (Generative Pre-trained Transformer) and FLAN (Flexible Language Acquisition Network) have gained significant prominence as foundational components in various AI applications. These models are created by training a machine learning architecture called a "Transformer" on vast amounts of natural language data. Within the context of this PhD research, we will conduct an extensive literature review to explore maintenance optimization techniques and investigate the potential of large language models in addressing the intricacies of decision-making in maintenance processes.

To achieve this, we will develop a novel framework that leverages the capabilities of large language models to optimize maintenance strategies. We will collect and pre-process relevant data, which will be used to train the language model(s) and validate the effectiveness of the framework. Furthermore, comprehensive experimental evaluations will be conducted to compare the performance of the language model-based approach against existing techniques commonly used in the field. Collaboration with industry partners will be instrumental in applying the developed framework to real-world maintenance scenarios, enabling an assessment of its practical effectiveness.

Throughout the course of this research, students involved in the project will utilize open-source tools for the development of these large language models. This will provide them with direct exposure to these tools, relevant literature, and a comprehensive understanding of general concepts and methods in machine learning.

The University of York takes great pride in its placement within the top ten UK universities in the REF, affirming our commitment to research excellence with social impact. Our vision aligns with being a University for the Public Good, fostering strong partnerships to expand and disseminate knowledge for local and global benefit. This project's overarching ambition and potential impact on future maintenance perfectly align with our principles of inclusion, internationalism, and collaboration.

Entry requirements:

Candidates should have (or expect to obtain) a minimum of a UK upper second class honours degree (2.1) or equivalent in Engineering, Physics, Computer Science, Mathematics or a closely-related subject.

How to apply:

Applicants should apply via the University’s online application system at https://www.york.ac.uk/study/postgraduate-research/apply/. Please read the application guidance first so that you understand the various steps in the application process.


Engineering (12)

Funding Notes

This is a self-funded project and you will need to have sufficient funds in place (eg from scholarships, personal funds and/or other sources) to cover the tuition fees and living expenses for the duration of the research degree programme. Please check the School of Physics, Engineering and Technology website for details about funding opportunities at York. View Website

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