Job Description

• School of Engineering, College of Science & Engineering
• Electronic and Electrical Engineering
• Lecturer: Grade UE08: £43,414 - £51,805 per annum
• Senior Lecturer: Grade UE09: £54,949 - £61,823 per annum
• Open-ended: Permanent
• Full-time: 35 hours per week

The successful candidate appointed will conduct research in the area of machine learning (AI) and computer vision for health in the Research Institute for Digital Communications (IDCOM) and participate in teaching and administration in Electronics and Electrical Engineering, contributing to the intellectual wealth and collegiate environment of the School of Engineering.

The successful candidate will be a good communicator who is able to inform and enlighten both undergraduate and postgraduate students. You will have a growing research portfolio in AI and computer vision for health, providing evidence of collaborative working, attracting external research funding and producing significant outputs. You will have demonstrated applications of your research in (but not limited to) one or more of the following domains: a) medical image reconstruction and processing (e.g. accelerated imaging in CT, MRI, US, PET, artifact correction, denoising); b) medical or biomedical image analysis for extraction of biomarkers; c) computer assisted interventions and how these may inform the future of surgery.

You will have demonstrated skills in supporting and motivating people (students and colleagues) and be able to plan and organise resources effectively. You will have demonstrated the ability to deliver research project results and/or effective learning programmes with high-quality publications, knowledge exchange and innovation built in as appropriate.

The Opportunity

We are looking to recruit potential leaders to play a major role in furthering our activities in research and teaching within Electronic & Electrical Engineering (E&EE). The successful candidate will undertake teaching duties in Electronics and Electrical Engineering with a specific focus in machine learning, digital and statistical signal processing, and related subject areas. You will also carry out research in machine learning and computer vision for health, and will have demonstrated applications of their research in (but not limited to) one or more of the following domains: a) medical image reconstruction and processing (e.g. accelerated imaging in CT, MRI, US, PET, artifact correction, denoising); b) medical or biomedical image analysis for extraction of biomarkers; c) computer assisted interventions and how these may inform the future of surgery. The candidate will be a member of the Institute for Digital Communications in the School of Engineering at the University of Edinburgh.

Your skills and attributes for success:

• A reputation in the of field machine learning (AI) and computer vision for health, (demonstrated by published results from research, publication in peer reviewed journals and appropriate high-calibre conference venues, recognition among research users and/or industry, etc.); specific areas of interest include applications of your research in (but not limited to) one or more of the following domains: a) medical image reconstruction and processing (e.g. accelerated imaging in CT, MRI, US, PET, artifact correction, denoising); b) medical or biomedical image analysis for extraction of biomarkers; c) computer assisted interventions and how these may inform the future of surgery.
• An ability to design effective learning programmes and to effectively deliver integrated curricula and assessment.
• Contribution to attracting external research funding and/or other financial support.
• Excellent communication, presentation and organisational skills and high proficiency in written and oral English language.
• Hold a Doctorate in a STEM related subject, or equivalent.

This role is UE08/UE09 and is available on a full-time, open-ended contract. The level of appointment for the position will be determined by the selection panel.

A full list of main responsibilities and the knowledge, skills and experience required for the role can be found in the full job description below

• Lecturer in AI and Computer Vision for Health (UE08) full job description »
• Senior Lecturer in AI and Computer Vision for Health (UE09) job description »

For informal discussion, potential candidates are invited to contact the Head of School, Prof Conchúr Ó Brádaigh at +44 131 650 5566 or HoS.Eng@ed.ac.uk, Director of Discipline for Electronic and Electrical Engineering, Dr James Hopgood at +44 131 650 5571 or James.Hopgood@ed.ac.uk.