Lecturer in Applied Artificial Intelligence for Engineering
- Recruiter
- CRANFIELD UNIVERSITY
- Location
- Cranfield, United Kingdom
- Salary
- Salary level 6 - range £43,351 to £48,323 per annum with potential progression to £60,403 per annum
- Posted
- Tuesday, 16 February 2021
- End of advertisement period
- Sunday, 14 March 2021
- Ref
- 3537
- Academic Discipline
- Engineering & Technology, Computer Science, Mechanical & Aerospace Engineering
- Contract Type
- Permanent
School/Department School of Aerospace, Transport and Manufacturing
Based at Cranfield Campus, Cranfield, Bedfordshire
Hours of work 37 hours per week, normally worked Monday to Friday. Flexible working will be considered.
Contract type Permanent
Salary Salary level 6 - range £43,351 to £48,323 per annum with potential progression to £60,403 per annum
Apply by 14/03/2021
Role Description
Cranfield University School of Aerospace, Transport and Manufacturing welcomes applications from prospective teaching focused faculty position in Applied Artificial Intelligence (AAI) for engineering, as part of the Centre for Autonomous and Cyberphysical Systems.
Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships is creating leaders in technology and management globally. Our distinctive expertise is in our deep understanding of technology and management and how these work together to benefit the world.
About School of Aerospace, Transport and Manufacturing
The School of Aerospace, Transport and Manufacturing (SATM) is a leading provider of postgraduate level engineering education, research and technology support to individuals and organisations. At the forefront of aerospace, manufacturing and transport systems technology and management for over 70 years, we deliver multi-disciplinary solutions to the complex challenges facing industry.
Our reputation for leading in the field of autonomous vehicle systems, applied artificial intelligence and control engineering has been established through more than thirty years of research into this field. We cover all types of autonomous vehicles including airborne, ground and marine as well as space.
About the Role
The Applied AI (AAI) group is a newly established group that sits within the Centre for Autonomous and Cyber-Physical Systems (CACPS). The centre hosts the AAI MSc, which offers both Full Time (FT) and Part Time (PT) education. In its inaugural year, it attracted over 20 students and is growing rapidly.
The AAI MSc particularly caters for engineering background students that want to learn machine learning for digital engineering transformation. The AAI research we conduct covers foundational strategic research programs funded by EPSRC and H2020, as well as a number of applied InnovateUK projects.
There will be opportunity to supervise both MSc and PhD students.
As a teaching focused lecturer, you will contribute to the teaching (65%) and research (25%) activities of the Centre for Autonomous and Cyber-Physical Systems, especially concerning the specific AAI MSc course described. Duties include: (a) managing the course (FT and PT), (b) teaching a number of modules in the AAI MSc and supporting other MSc modules, (c) conducting collaborative research.
You will also be expected to collaborate with the existing staff working in the area and have communications and meetings with our collaborators within the university or in other international universities.
About You
You will be educated to doctoral level in a relevant subject and have experience of management teaching courses and degree programs at the MSc level. With excellent communication skills, you will have expertise in digital engineering, machine learning, and data science will be advantageous.
Our Values
Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. Find out more here. We aim to create and maintain a culture in which everyone can work and study together and realise their full potential.
Diversity and Inclusion
Our equal opportunities and diversity monitoring has shown that women and minority ethnic groups are currently underrepresented within the university and so we actively encourage applications from eligible candidates from these groups.
Flexible Working
We actively consider flexible working options such as part-time, compressed or flexible hours and/or an element of homeworking, and commit to exploring the possibilities for each role. Find out more here.