KTP Associate in partnership with Fathom Systems

The Department of Electronic and Electrical Engineering, Institute of Signal, Systems and Communication at the University of Strathclyde in partnership with Fathom Systems (www.fathomsystems.co.uk) seek to appoint a Knowledge Transfer Partnership (KTP) Associate in the area of predictive analytics and edge computing for health condition monitoring. The KTP is a trilateral collaborative project between the Associate, the University and a company partner (see www.ktpws.org.uk).

Fathom Systems is a commercial diving company which develops systems for saturation diving with business operations worldwide. They have over 10-years expertise in the design, manufacture and sale of specialised control & communications systems, monitoring and gas analysis equipment for deep sea diving. Fathom Systems is developing their Critical System Monitoring and Tracking System (CSMTS) products and services for the global commercial diving industry targeting Self-Propelled Hyperbaric Lifeboats.

As a KTP Associate you will be principally based at Fathom Systems in Portlethen, Aberdeenshire but you will spend periods of time at the University of Strathclyde as required. You will work jointly with Strathclyde and Fathom Systems to apply emerging machine learning and analysis of data, selection and integration of sensors and communications technologies to enhance diver health condition monitoring and build intelligence with powerful prognostics capabilities. You will be required to disseminate high-quality research output through the appropriate reporting channels.

In addition to the KTP core development training, you will have a dedicated budget of £6,000 for further training and career development and a pathway to obtain Chartered Management Institute (CMI) level 5 qualification in Management. Additionally, you will have the opportunity to enrol for a part time MPhil/PhD with the Department of Electronic and Electrical Engineering at Strathclyde University.

To be considered for the role you will be educated to a minimum of 2:1 BSc level in an Engineering, Computer Science, Mathematics or Physics related area or you will be educated to Degree level in a relevant field with significant, relevant experience. You will have a strong mathematical and programming background with experience in machine learning, artificial intelligence and predictive analytics, understanding in sensors and communications. You will be capable of high-level problem solving and be capable of working effectively as part of a team and on your own initiative.

Supported by the academic team at the University of Strathclyde, the KTP Associate will deliver research activities in the area of machine learning and data analytics on sensor data provided by the partner company. To lead the development and integration of sensor and communication technologies to the Critical System Monitoring and Tracking System and develop edge computing software to enhance diver health condition monitoring.

For full details please click here and search for vacancy (95890)