Ultrasonic Antifouling System Development Engineer (KTP Associate)

Teesside University
Gateshead, United Kingdom
11 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Compensation
£ 40K

Job location

Gateshead, United Kingdom

Tech stack

Artificial Intelligence
Data analysis
Artificial Neural Networks
Comsol Multiphysics
Matlab
Systems Development Life Cycle
KTP
Optimization Algorithms
Ansys

Job description

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., * 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

Requirements

Do you have experience in MATLAB?, Do you have a Master's degree?, * A master's degree (or equivalent experience) in Mechanical, Acoustic, Marine, or Mechatronic Engineering, or a closely related discipline.

Modelling:

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

AI and Data Analysis:

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

Prototype Design and Testing:

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

Collaboration and Analytical Skills:

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

Individual Traits Required:

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

Desirable:

  • Knowledge of ultrasonic antifouling 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.

Benefits & conditions

  1. Technology and Methodology Familiarisation for AI Driven Ultrasonic Anti-fouling modelling (UAFM) Platform design.

  2. Development, Optimisation, and Digital Validation of the Computational UAFM Platform.

  3. Design and Setup of a Scaled-Down Marine-Growth Experimental System.

  4. (UAFM) Platform - Validation via Full Optimisation of OES's hybrid ultrasonic antifouling system prototype for biofouling prevention and removal.

  5. Intelligent System Deployment and Long-Term Operational Evaluation Summary

  6. 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.

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