Assistant Professor in Machine Learning
- Education and Research Focused
- Work with our Faculty of Science and Technology
- Academic Level B/C, Salary Range $95,419 - $133,970 + 17% Super
The University of Canberra is seeking an Assistant Professor in Machine Learning to join the Faculty of Science and Technology. This role will see you contribute to the research and teaching efforts within Machine Learning. You will design and deliver undergraduate and postgraduate units in Machine Learning and other activities that will directly impact a student’s learning experience.
Reporting to the Discipline Lead, you will be required to develop an active research program and commit to student learning through coordination and delivery of units. Additionally, your ability to collaborate and consult with students will be critical to the success of this role.
In order to be considered, you will possess the necessary qualifications preferably a PhD and possess expertise in research development. As an experienced teaching professional, you will have a track record in unit and course material design and development. You must demonstrate your ability to communicate with various levels of stakeholders and show your strong organisational abilities.
In return, you will have the opportunity to will be part of a dynamic world class University that values research, teaching, innovation and collaboration, a University with a Global focus and strong international links, including partnerships with Universities around the World. You will also work with a university named in the World’s Top 100 Young Universities ranking for 2018 by The Times Higher Education. The University is an EO employer offering excellent conditions and benefits such as flexible, family-friendly policies; on site gym, on site medical services supermarket and childcare facilities.
The University of Canberra is committed to achieving a diverse workforce and strongly encourage applications from Aboriginal and Torres Strait Islander people.
To be considered for this position your application must include your resume and cover letter.
Closing Date: 11:55 pm, Saturday January 5th 2019
Recruitment and application questions: please contact Sobana Nathan, Talent Acquisition Partner on 02 6206 8789 or email Sobana.email@example.com.