CRANFIELD UNIVERSITY

Lecturer in Applied Artificial Intelligence for Engineering

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
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.

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