KTP Associate – Computer Vision Marine Monitoring Specialist

Are you looking to apply your AI, machine learning, and computer vision expertise in a real-world setting to drive innovation in marine environmental monitoring? 

The Role:

A unique and exciting opportunity has arisen for a Knowledge Transfer Partnership (KTP) Associate to work with MSeis Limited and the University of Plymouth on a ground-breaking project integrating AI-driven computer vision technology into advanced dual-sensor marine monitoring systems. This collaboration aims to enhance marine mammal detection, hazard mitigation, and environmental sustainability in offshore operations. Range and bearing determination of targets.  You will be based in Weston-Super-Mare, Somerset.  For more information about how Knowledge Transfer Partnerships can accelerate your career, visit: https://iuk-ktp.org.uk/

The Candidate:

You must meet with the following essential criteria:

• MSc/PhD in Computer Science, AI, Machine Learning, or a related field.
• Strong programming skills in Python and experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Knowledge of computer vision, object detection, and real-time image processing.
• Experience working with multimodal sensor data and AI model integration.
• Excellent problem-solving skills and the ability to apply AI techniques to real-world challenges.

The following desirable criteria would be advantageous:

• Experience in marine monitoring, environmental sensing, or offshore operations.
• Familiarity with embedded systems and optimizing AI models for real-time deployment.
• Knowledge of environmental regulations related to marine life protection.
• A clear understanding of project management including project planning, cost control, risk assessment, quality and resource management.

The Company:

MSeis is a specialist marine technology company dedicated to designing, building, and deploying hydrophone systems, passive acoustic monitoring solutions, and dual-sensor thermal-optical camera systems for environmental monitoring. By integrating AI and machine learning into its cutting-edge technologies, MSeis is transforming offshore marine safety and conservation. More information about MSeis can be found at www.mseis.com

There is an essential requirement within this role that you will be required to travel to and work at different University sites and/or other business locations that may not be easily accessible by public transport. Please refer to the job description for further information.

For an informal discussion to find out more about the role then please contact:

Ioanna (Yana) Papanikolaou – ioanna.papanikolaou@plymouth.ac.uk

Interviews will take place at MSEIS premises at Weston Super Mare and  are likely to take place week between 25^th August to 5^th September.

This is a full-time position working 37 hours per week on a fixed-term basis for a period of 24 months due to funding.

Flexible working options including job share will be considered.

Due to the nature of the role, unfortunately we are unable to accommodate working from home.

Please apply online, demonstrating how you meet the essential criteria outlined in the knowledge, qualifications, training, and experience elements of the job description in your supporting statement.

A successful external candidate for this position would be employed by the University of Plymouth Services Limited, a wholly owned subsidiary of the University of Plymouth. Employees of the University of Plymouth Services Limited work alongside the University of Plymouth colleagues in delivery of Plymouth’s strategic vision, and will adopt the University of Plymouth’s HR policies and procedures in full unless otherwise stated.

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