Ultrasonic Antifouling System Development Engineer; KTP Associate

• Project manage the delivery of the Knowledge Transfer Partnership work plan (with extensive support from both company and academic supervisors), which includes the following stages:
  • Business and Process Familiarisation, Planning, and Risk Management Summary
  • Technology and Methodology Familiarisation for AI Driven Ultrasonic Anti-fouling modelling (UAFM) Platform design.
  • Development, Optimisation, and Digital Validation of the Computational UAFM Platform.
  • Design and Setup of a Scaled-Down Marine-Growth Experimental System.
  • (UAFM) Platform – Validation via Full Optimisation of OES’s hybrid ultrasonic anti-fouling system prototype for biofouling prevention and removal.
  • Intelligent System Deployment and Long-Term Operational Evaluation Summary
  • Commercial Demonstration, Knowledge Transfer, and Exploitation Plan Development Summary.
• Co-author and present academic papers to relevant journals/conferences.
• Contribute to KTP evaluation and final reports.
• Adhere to the University’s & Associate OES Group Ltd.’s Health and Safety Policy and guidelines.
• Adhere to the General Data Protection and The Data Protection Act 2018.
• Promote Equality and Diversity for staff and students and embrace the Values and Behaviours Frame
• Any other reasonable duties that may be allocated from time to time commensurate with the grading of the post.

A master’s degree (or equivalent experience) in Mechanical, Acoustic, Marine, or Mechatronic Engineering, or a closely related discipline.

Proven experience in dynamic modelling using tools such as COMSOL, ANSYS, or MATLAB.

Familiarity with data-driven modelling, optimisation algorithms, or machine learning techniques (e.g. Bayesian optimisation, surrogate models) to support predictive system design and control.

Hands-on experience in experimental setup, sensor integration, and data acquisition for acoustic or vibration testing.

Strong teamwork, communication, and analytical problem-solving abilities in multidisciplinary environments.

Self-motivated, methodical, clear communicator, and results oriented.

• Knowledge of ultrasonic anti-fouling systems, wave propagation, acoustic optimisation, marine biofouling, and related environmental compliance (e.g., DEFRA, IMO).
• Experience developing control interfaces or dashboards.
• Knowledge of physics-informed neural networks (PINNs).
• A PhD in a relevant discipline.

The purpose of this project is to create and integrate an AI enabled, multi physics acoustic and hydrodynamic modelling platform that strengthens OES Group’s product development and supports the design of next generation intelligent ultrasonic systems that sustainably prevent and remove marine biofouling.

OES Group Ltd specialises in designing and manufacturing advanced corrosion and anti-fouling solutions for the offshore, maritime, and renewable energy sectors. Their technologies help protect high-value assets by cutting maintenance demands, reducing fuel consumption and emissions, and ultimately extending the lifespan of critical equipment. Their innovative technologies include the deployment of Ultrasonic Anti-Fouling (UAF) systems. These systems use high-frequency sound waves delivered through ultrasonic transducers to create microscopic vibrations providing an environmentally friendly alternative to traditional chemical-based anti-fouling methods.