Computer Vision Expert
4 days ago
At Robert Gordon University, we are seeking a highly motivated and talented Computer Science Graduate to join our team as a KTP Associate. This exciting opportunity is designed to fast-track your career development in Machine Learning with a specific focus on Deep Learning for Video Analysis and Computer Vision related tasks.
This 2-year project is a collaborative effort between RGU and Fennex Ltd, jointly funded by Innovate UK and Fennex. As a KTP Associate, you will be responsible for pre-processing and analysing video data, training advanced AI models capable of tracking and detecting objects in real-time or near real-time, and anticipating potential hazards to improve safety.
You will work closely with the team at Fennex to understand their specific requirements and receive extensive practical and formal training, gaining marketable skills, broadening your knowledge and expertise within an industrially relevant project, and gaining valuable experience from industrial and academic mentors.
The ideal candidate must have at least a First-Class Honours degree in Computing, Machine Learning, AI, or a strongly related field. Strong programming skills and a genuine enthusiasm for applying advanced methods to a real-world problem are essential. A postgraduate degree or higher would be highly desirable.
The salary range for this position is £35-38k, plus a £4000 training budget. You will work full-time for 37 1⁄2 hours per week, typically 8:30 to 17:00 with breaks. Annual leave is 29 days per year.
This role may be eligible for sponsorship under the Skilled Worker route. For KTPs, we will also consider eligibility under the Global Talent Visa route.
Key Responsibilities:
- Transfer knowledge of data science and state-of-the-art machine learning techniques to Fennex.
- Develop a set of methods for exploration, visualising, pre-processing, and handling large volumes of videos related to safety in the Oil and Gas Sector.
- Design, implement, and evaluate intelligent and data-driven methods for recognising and anticipating specific actions within videos.
- Create and evaluate anomaly detection methods using state-of-the-art machine learning and deep learning models.
- Develop tools to embed the above directly into one of Fennex's HSE solutions (Microsoft, Azure based).
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