Machine Learning & Data Fusion Associate (KTP Associate)

Duties and Responsibilities

1. Analyse and implement the latest practical approaches for object detection, tracking, decision-making, and multimodal data fusion.
2. Collaborate with academic and industry supervisors to develop, refine, and implement a detailed project plan and timeline.
3. Utilise machine-learning techniques to design, train, and validate deep-learning models addressing the project’s challenges.
4. Develop and curate datasets required for training and validating deep-learning models.
5. Prototype and evaluate the developed implementations against defined performance metrics, assessing their feasibility for real-time applications.
6. Monitor and support the delivery of product features into a customer facing environment.
7. Monitor and document the on-going impact of new product features in sales and estimate the impact of new sales on gross value added (GVA).
8. Understand and document improvements in business competitiveness and the impact of new developments within the company. (For example, up-skilling of other staff, the creation of new positions, strategic changes, and new business opportunities.)
9. Where appropriate, drive significant change and help the business to identify new opportunities.
10. Document and report findings from development and evaluation phases to academic and business partners, including recommendations for further development.
11. Support compliance with governance guidelines and regulations in conducting methods development and evaluations.
12. Participate in regular progress meetings with business and academic supervisors and contribute reports and presentations to the Local Management Committee (LMC) and project stakeholders.
13. Contribute to the development of technical reports, presentations, and publications related to the project’s outcomes.
14. Support the dissemination of project results through conferences, workshops, and industry events.
15. Collaborate with business partners to integrate feedback and optimize the custom design for practical application.

To develop novel methods of enabling detection of drones in flight.

The project will pioneer methods to detect and track moving objects in three-dimensional space. This will be achieved through a data-driven approach applying machine-learning algorithms to reliably detect, track, and classify objects across diverse conditions and environments.