Research Assistant in LLM for Fault Diagnosis of Energy Systems

## Exciting Research Opportunity: LLMs for Renewable Energy Fault Diagnosis at the University of Surrey

The University of Surrey stands as a beacon of innovation, fostering a global community dedicated to transformative education and impactful research. With an ambitious vision to be among the world's leading universities, Surrey empowers its employees to contribute significantly to this overarching goal, making a tangible difference both individually and collectively. The institution cultivates a culture of empowerment, where talent and dedication are paramount to achieving remarkable outcomes.

This particular role presents a unique and compelling opportunity for a motivated Research Assistant in Large Language Models (LLMs) for Fault Diagnosis of Energy Systems. This position is a key component of an EPSRC Supergen Network+ project, focusing on Artificial Intelligence for Renewable Energy, generously funded by the University of Warwick. It offers a chance to immerse yourself in cutting-edge research at the nexus of Renewable Energy Systems, Artificial Intelligence (AI), and Prognostics and Health Management (PHM).

As part of the esteemed Energy Research Cluster within the School of Engineering, you will be instrumental in developing sophisticated, data-driven frameworks designed to enhance the resilience and sustainability of our vital renewable energy systems and infrastructure. This is a part-time position, requiring 14.4 hours per week, offering a flexible approach to contributing to groundbreaking work.

Key Responsibilities and Contributions:

• Pioneering LLM Development: You will be at the forefront of developing LLM-based models for the critical tasks of fault detection, diagnosis, and predictive maintenance within renewable energy systems.
• Advanced Data Integration: Contribute significantly to the design and implementation of sophisticated data pipelines, seamlessly integrating diverse data sources such as sensor readings, maintenance logs, and crucial domain knowledge.
• Rigorous Evaluation and Best Practice: Conduct thorough experiments, meticulously evaluate model performance, and play a vital role in establishing best practices for LLM-enhanced prognostics.
• Industry Collaboration: Engage with industry partners to facilitate the translation of cutting-edge research outputs into practical, deployable tools.
• Dissemination of Knowledge: Prepare comprehensive scientific reports, contribute to impactful publications, and present your research findings at both internal and external forums.
• Project Support and Reproducibility: Provide essential support for ongoing project development, including meticulous dataset curation, clear documentation, and the establishment of robust, reproducible research workflows.

What You Bring to the Role:

This role is ideally suited for individuals with a strong academic foundation and a genuine passion for applying AI to complex engineering challenges. The ideal candidate will possess:

• A degree in Engineering, Computer Science, AI, Data Analytics, or a closely related discipline.
• Proficient programming skills in Python, coupled with familiarity with established LLM frameworks.
• Demonstrated experience in machine learning, natural language processing, or time-series modelling.
• A compelling interest and enthusiasm for applying AI techniques to address challenges within engineering and energy systems.

Career Advancement and Development:

This position offers a significant advantage for candidates looking to deepen their expertise in two of the most dynamic fields: Artificial Intelligence and Renewable Energy. Working within a leading research institution, you will gain invaluable hands-on experience with state-of-the-art LLM technologies and their practical application to critical infrastructure. The opportunity to collaborate with industry partners provides a unique pathway to understand real-world challenges and contribute to solutions that have immediate impact. Furthermore, the emphasis on scientific reporting and publication will be instrumental in building a strong research portfolio, a crucial asset for any aspiring academic or research professional. This role is an excellent stepping stone for those seeking to advance their careers in AI research, sustainable energy solutions, or prognostics and health management.

Key Considerations for Applicants:

• Part-Time Commitment: The role is part-time (14.4 hours/week), which may appeal to those seeking to balance other commitments or pursue ongoing studies.
• Fixed-Term Contract: The position is a fixed-term contract until June 2026, offering a defined period for intensive research and development.
• Pro-rata Salary: The annual salary is £13,844 per annum (pro rata for 0.4 FTE), reflecting the part-time nature of the role.
• Application Process: Prospective candidates are required to submit a CV and a compelling cover letter through the university's online recruitment portal.
• Interview Stage: Shortlisted candidates will be invited for an interview, which will include a technical discussion and an opportunity to showcase relevant previous work.
• Commitment to Diversity and Inclusion: The University of Surrey is deeply committed to fostering an inclusive environment. Applications are particularly encouraged from individuals belonging to under-represented groups, including Black, Asian, and minority ethnic groups, and individuals with disabilities.

This is more than just a research position; it's an invitation to be part of a forward-thinking institution driving innovation in fields critical to our planet's future. If you are a driven and curious individual with a passion for AI and renewable energy, we encourage you to explore this exciting opportunity.