Edinburgh Napier University – Schools of Computing and Engineering & the Built Environment
Salary: £40,927 to £50,296 per annum (Grade 6)
Edinburgh Napier University is the ‘#1 Modern University in Scotland’. An innovative, learner centric university with a modern and fresh outlook, Edinburgh Napier is ambitious, inclusive in its ethos and applied in its approach.
The Schools of Computing and Engineering & the Built Environment have around 200 academics, 3,100 campus-based students, and deliver programs with professional accreditations from the British Computer Society, Institution of Engineering and Technology, The Chartered Institute of Building and other accreditation bodies. We have excellent computing, engineering and construction lab facilities. The two schools are embarking on a joint major development in the area of Industry 4.0, bringing together computer science, engineering, mathematics and construction technology. The School of Computing is highly regarded and one of the UK’s largest computer science departments. The School of Engineering & the Built Environment houses leading UK research centers in transport policy and sustainable construction. The schools are based in the lively and exciting Merchiston area at the heart of Edinburgh, Scotland’s inspiring capital.
This is a great opportunity for an academic with expertise in Artificial Intelligence and Machine Learning or related fields to join the Artificial Intelligence research group where you can add to the work of the experienced team exploring Evolutionary Robotics, Healthcare Data Analytics, Smart Transport Applications and Machine Learning Enabled Cyber Security. Areas of desirable expertise include, but are not limited to: machine learning with applications to robotics, machine learning theoretical foundations, machine learning applied to biomedical data, machine learning for transport systems, deep learning systems, adversarial machine learning, generative models in machine learning . With 80% time allocation for research, this role will allow you to explore novel and emerging areas of artificial intelligence and machine learning, deliver excellent quality research papers and secure substantial external research funding.
The Lecturer in Artificial Intelligence and Machine Learning will contribute to and build programs and modules to support the expansion of the School’s teaching portfolio which explores the changing nature of IT infrastructure, AI and ML applications to big data, business intelligence, and the impact of technology on business. You will actively contribute to our existing portfolio of computer science based degree programmes.
We are looking for someone who can demonstrate enthusiasm for working in a cross-disciplinary manner in fundamental and applied research and in the development of research-informed teaching to enhance employability of our graduates. You will have the opportunity to expand your industry connections through our existing networks and by visiting students on one-year industry placements and on our employer-based Graduate Apprentice programme.
Further information about Edinburgh Napier University can be found here.
As a lecturer you will be a member of our Artificial Intelligence research group with:
- A research allowance of 80% of your time to build your research.
- Access to our staff development budget for travel to conferences and to establish collaborations.
- Extensive research training and development through our Research, Innovation and Enterprise Office (RIE).
- You will also study towards a Post Graduate Certificate in Teaching and Learning leading to Fellowship of the Higher Education Academy.
- Support for grant applications from colleagues in the school and the university.
- Join or lead a PhD student supervisory team.
- A fully funded PhD position (UK student) that you are expected to fill during your first year of employment at Edinburgh Napier University.
Applicants must demonstrate:
- A doctoral level qualification in the relevant discipline.
- Evidence of a professional academic and research profile alongside a commitment to sustained continuous professional/academic development.
- Evidence of a developing research track record appropriate for career stage in the research area of Artificial Intelligence and Machine Learning (high quality outputs, potential for getting external research funding, engagement in scientific and professional societies, organization of conferences and workshops, reviewing papers for scientific conferences and journals).
- Evidence of a teaching experience appropriate for the career stage.
- A level of achievement appropriate to the post being applied for, including international/ national standing and academic leadership.
Applicants will preferably also demonstrate:
- A developing track record of internationally excellent output in interface areas of computer science, engineering, construction and mathematics that are relevant for Industry 4.0 research.
If you would like to know, more about this exciting opportunity please click here to view the role profile.
Further information about our benefits can be found here.
Informal inquiries about the role can be made to Professor Peter Andras (email@example.com) or Professor Ben Paechter (firstname.lastname@example.org).’
For general recruitment queries, please contact email@example.com
Applications for the role must be submitted via the Edinburgh Napier University job applications web site – emailed applications will not be accepted.
Application closing date: 29th May 2022 @ 11:59 pm
Interview Location: Edinburgh Napier University, Merchiston Campus, Edinburgh, Scotland
Interview date: Face to face interviews will be scheduled once the shortlisted candidates have been advised by the panel. You will be supported by our dedicated staff to arrange the logistics to attend these interviews.
The University is committed to inclusion, demonstrated through our work in respect of our diversity awards and accreditations and holds Disability Confident, Career Positive and Stonewall Scotland Diversity Champion status. More details can be found here.