Lecturer in Agricultural Data Science, Education Focused
5 days left
- Full Time
- Opportunity to provide leadership in the teaching of Agricultural Data Science within an education focused environment
- Located on the Camperdown Campus at School of Life and Environmental Sciences
- Full time, Level B fixed term, 2 years, offering a base salary of $110K p.a., plus leave loading and generous employer's contribution to superannuation.
About the opportunity
An opportunity exists for a highly motivated Lecturer in Agricultural Data Science (Education-focused). The successful candidate will support and coordinate undergraduate Units of Study and also undertake curriculum development and innovation. They will understand the principles and pedagogy of quality teaching and the student experience. They will have a demonstrated ability to deliver quality educational experiences for students, facilitating and guiding their learning. The position will also assist the academic coordinators of other units within the discipline.
Your key responsibilities will be to deliver high quality educational experiences for students in data science within an applied statistics teaching program in the School, and work with colleagues to improve offerings within the theme. You may also be required to support teaching of spatial science and first year agricultural and environmental science units.
To learn more about the School of Life and Environmental Sciences, click here
The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for Lecturer in Agricultural Data Science (Education-focused) who has:
- a PhD in Data Science or closely-related quantitative field
- significant experience in teaching and learning in a tertiary environment, as evidenced by participation in team teaching within an established program and experience in teaching in a variety of settings
- demonstrated success in designing, implementing and evaluating teaching and learning initiatives
- a strong interest in the development and evaluation of innovative practices in teaching and learning with a view to improving educational outcomes
- demonstrated experience coordinating or supporting coordination of a unit of study within Data Science or a closely-related quantitative field.
- the capacity to contribute to teaching of spatial science and introductory agricultural and environmental science units
- familiarity and experience with Work Health and Safety requirements for laboratory and field work
Closing date for applications
11:59 pm, 26 January 2021
Please note: The University of Sydney will be closed from 24 December 2021 until 9 January 2022 inclusive.
To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.
Sponsorship / work rights for Australia
Please note: Visa sponsorship is only available for this position for candidates who are currently located within Australia.
Australian Temporary Residents currently employed at the University of Sydney may be considered for a fixed term contract for the length of their visa, depending on the requirements of the hiring area and the position.
Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.
The University of Sydney is committed to diversity and social inclusion. Applications from people of culturally and linguistically diverse backgrounds; equity target groups including women, people with disabilities, people who identify as LGBTIQ; and people of Aboriginal and Torres Strait Islander descent, are encouraged.
How to apply
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