KTP Associate – Computer Vision Marine Monitoring Specialist
| Dyddiad hysbysebu: | 30 Mai 2025 |
|---|---|
| Cyflog: | Heb ei nodi |
| Gwybodaeth ychwanegol am y cyflog: | Salary: £29,000 – £30,805 per annum (depending on experience) – (plus £4,000 personal development budget) – KTP |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 29 Mehefin 2025 |
| Lleoliad: | Weston-Super-Mare, North Somerset |
| Gweithio o bell: | Ar y safle yn unig |
| Cwmni: | University of Plymouth |
| Math o swydd: | Dros dro |
| Cyfeirnod swydd: | B0727 |
Crynodeb
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
University of Plymouth:
The University of Plymouth is renowned for its research excellence in marine science, artificial intelligence, and environmental monitoring. The KTP project will be supported by leading academics, including Dr. Lauren Biermann (Marine & Coastal Remote Sensing Lecturer), Dr. Haoyi Wang (Lecturer in Computer Science), and Dr. Dena Bazazian (Lecturer in Machine Vision and Robotics). Their expertise spans AI-driven environmental monitoring, multimodal data integration, and computer vision applications for marine conservation. The University of Plymouth provides a strong foundation for interdisciplinary research and innovation, ensuring the successful knowledge transfer of cutting-edge AI technology into real-world applications.
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 25th August to 5th September and you will be notified if you have been shortlisted or not.
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.
For more information about the job and the person specification, please refer to the job description.
Application Process
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.
Following the closing date of the vacancy, you will be notified on the outcome of your application in due course.
Our Offer
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.
When joining us, you will receive:
• Generous annual leave: 25 Days Annual Leave plus Bank Holidays & Closure Days
• Generous pension scheme
• Cycle to Work & Electric Car Scheme
• Employee Assistance Programme
• Development opportunities
• Enhanced family leave
• Flexible working
• Retailer discounts
• On-site nursery (Plymouth Campus)
A summary of our comprehensive benefits can be viewed here.
Additional Information
The University of Plymouth is an inclusive community where everyone is welcomed regardless of their background. To find out more about our inclusive community initiatives, such as Athena Swan and the Race Equality Charter, please visit our Equality, Diversity and Inclusion webpages.
We particularly welcome applicants from under-represented communities at the University of Plymouth, such as people with disabilities, ethnically diverse and LGBT+.
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
University of Plymouth:
The University of Plymouth is renowned for its research excellence in marine science, artificial intelligence, and environmental monitoring. The KTP project will be supported by leading academics, including Dr. Lauren Biermann (Marine & Coastal Remote Sensing Lecturer), Dr. Haoyi Wang (Lecturer in Computer Science), and Dr. Dena Bazazian (Lecturer in Machine Vision and Robotics). Their expertise spans AI-driven environmental monitoring, multimodal data integration, and computer vision applications for marine conservation. The University of Plymouth provides a strong foundation for interdisciplinary research and innovation, ensuring the successful knowledge transfer of cutting-edge AI technology into real-world applications.
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 25th August to 5th September and you will be notified if you have been shortlisted or not.
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.
For more information about the job and the person specification, please refer to the job description.
Application Process
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.
Following the closing date of the vacancy, you will be notified on the outcome of your application in due course.
Our Offer
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.
When joining us, you will receive:
• Generous annual leave: 25 Days Annual Leave plus Bank Holidays & Closure Days
• Generous pension scheme
• Cycle to Work & Electric Car Scheme
• Employee Assistance Programme
• Development opportunities
• Enhanced family leave
• Flexible working
• Retailer discounts
• On-site nursery (Plymouth Campus)
A summary of our comprehensive benefits can be viewed here.
Additional Information
The University of Plymouth is an inclusive community where everyone is welcomed regardless of their background. To find out more about our inclusive community initiatives, such as Athena Swan and the Race Equality Charter, please visit our Equality, Diversity and Inclusion webpages.
We particularly welcome applicants from under-represented communities at the University of Plymouth, such as people with disabilities, ethnically diverse and LGBT+.