Non-causal High Precision Marine Operations and Monitoring Based on Large Language Model
Project ID: 2531ad1561
(You will need this ID for your application)
Research Theme: Engineering
UCL Lead department: Mechanical Engineering
Lead Supervisor: Yao Zhang
Project Summary:
We are seeking a motivated PhD candidate to join a cutting-edge project focused on creating a large language model (LLM) specifically for the ocean environment. This project will lay the groundwork for advanced control and monitoring systems in high-precision marine operations, including offshore renewable energy platforms, multi-vessel formation control, and soft-body submarine technology.
The candidate will lead the development of this ocean-focused LLM, trained on vast datasets capturing marine dynamics, weather patterns, and oceanographic conditions. This model will enable non-causal predictive control, empowering real-time adjustments in marine activities and improving resilience against unpredictable environmental forces. The project’s end goal is to advance automation and reliability in marine technology, contributing directly to sustainable energy solutions and safe, efficient operations at sea.
The successful applicant will benefit from collaboration within an EPSRC-funded multi-modal AI network project (£1.8m), providing access to world-leading scientists and industry partners. Through this network, the candidate will gain exposure to multi-disciplinary insights, practical applications, and pioneering AI technologies, offering a unique environment for skill and career growth in AI-driven marine engineering.
If you are passionate about AI, marine technology, and renewable energy, this project offers a unique opportunity to lead innovation in ocean-based applications with far-reaching impacts on climate goals and maritime operations. Join us in advancing the future of sustainable marine solutions through AI.