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Lecturer\Senior lecturer in applied machine learning

Employer
University of Bristol
Location
Bristol, United Kingdom
Salary
Grade J - £38,587 - £43,434, Grade K - £44,706 - £50,296, Grade L - £53,348 - £60,022 per annum
Closing date
May 26, 2022
The role

The Faculty of Engineering at the University of Bristol is committed to leading engineering research and providing the highest level of education to Engineers of tomorrow. The Faculty has a strategic focus on applications of artificial intelligence and data science in engineering.

The Department of Mechanical Engineering is now looking to enhance their capability in research and providing up to date and relevant education in machine learning, applied in engineering. We are thus looking for someone with the ability and interest to conduct research and provide education in this area through provision of stimulating and authentic learning environments.

What will you be doing?

You will:
  • Conduct collaborative and individual research, apply for research funding and disseminate the results of the research through appropriate channels in the focus area of the role.
  • Preparing and updating learning content in a variety of digital formats to develop the education programme for engineering students.
  • Be responsible for the delivery of teaching and coordination of the relevant units as part of a multidisciplinary team to make sure that all students receive an excellent learning experience.
  • Supervise Bachelor's and Master's level projects in the focus area of the role.


You should apply if
  • You are excited about research and teaching in a successful Engineering Faculty in an internationally prominent research-led teaching University.
  • You have expertise in application of machine learning in engineering.
  • You value working within a diverse and multi-cultural team and are prepared to serve as a role model in inclusive workplace behaviours.
  • You understand the demands of the digital learning environment on the students' wellbeing and are prepared to embrace the blended model of teaching balancing in-person and remote learning activities for large and small groups of students.
  • You can build strong, effective relationships with a range of stakeholders within and beyond the University.
  • You have excellent communication skills and can clearly articulate verbally and in writing.
  • You are someone who can get up to speed quickly, thrives on digesting lots of information, is mindful of contrasting priorities, and can shape activities in a sustainable manner.


We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT+ and BAME communities, to join us.

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