School of Agriculture and Food Sustainability
Assist data management practices for satellite, UAV and ground-based phenotyping platforms.
1 full-time position until November 2027
Based across St Lucia and Gatton Campus
About UQ
As part of the UQ community, you will have the opportunity to work alongside the brightest minds, who have joined us from all over the world.
Everyone here has a role to play. As a member of our professional staff cohort, you will be actively involved in working towards our vision of a better world. By supporting the academic endeavour across teaching, research, and the student life, you will have the opportunity to contribute to activities that have a lasting impact on our community.
Join a community where excellence is at the core of our culture, contributions are valued and a range of benefits and rewards are available, such as:
26 weeks paid parental leave or 14 weeks paid primary caregiver leave
17% superannuation contributions
17.5% annual leave loading
Access to flexible working arrangements including hybrid working options, flexible start/finish times, purchased leave, and a condensed fortnight
Health and wellness discounts – fitness passport access, free yearly flu vaccinations, discounted health insurance, and access to our Employee Assistance Program for staff and their immediate family
On campus childcare options
Cheap parking (from just $5.75 a day)
Salary packaging options
About This Opportunity
The Australian Plant Phenomics Facility (APPF) was established in 2009 under the Australian Government’s National Collaborative Research Infrastructure Strategy (NCRIS) to develop a globally collaborative plant phenomics capability that provides leadership in infrastructure, skills and service for agricultural research and industry to maximise the productivity in Australia’s unique and variable environment.
The Research Assistant (Data Analyst) provides technical research support and subject matter expertise in support of activities coordinated by the UQ node of the Australian Plant Phenomics Facility (APPF) at all stages of the research life cycle.
Key responsibilities will include:
Coordinates and implements appropriate data management practices for the outputs of diverse phenotyping platforms in line with standards set out by the APPF,
Assists with the development, design and improvement of data processing pipelines derived from phenotyping platforms.
The management of software archives, repositories and databases associated with the project.
Assists in the development of dashboards and visualisation tools for datasets from multiple sources
Applies and/or instructs others on the application of advanced or specialist or technical research skills or processes, including computer vision, machine learning and data management.
Assists in the conduct of complex tasks involving all stages of the APPF data lifecycle.
Undertakes maintenance and upkeep of facilities and equipment; as well as troubleshoots issues with scientific/technical equipment
Contributes to the safe and efficient operation of research equipment, infrastructure, methodologies and protocols
Ensures the appropriate storage, handling and disposal of chemicals, equipment, stores and/or samples/specimens
Contributes to the safe and efficient operation of research equipment, infrastructure, methodologies and protocols
Ensures the appropriate storage, handling and disposal of chemicals, equipment, stores and/or samples/specimens
This is a full-time (100%), fixed-term position until November 2027.
At HEW level 5, the full-time equivalent base salary will be in the range $77,396.47 - $86,029.78, plus a generous super allowance of up to 17%. The total FTE package will be up to $90,553.87 - $100,654.84 annually. As these roles are covered by an Enterprise Agreement, you will also receive regular remuneration increases in line with the Enterprise Agreement.
About You
The candidate will have specialist technical research skills in areas such as computer vision and machine learning, experience in managing and troubleshooting complex datasets, specifically:
Completion of a degree level qualification in Information Technology, Software Engineering, Computer Science; or an equivalent combination of relevant experience and/or education/training
Excellent practical research skills and experience in relevant research methodology or techniques required for this body of research
Experience using Python, R, Linux/unix
Aware of Robot Operating System (ROS)
Ability to work collaboratively with colleagues
Ability to work independently on routine procedures
Excellent oral and written communication skills
Well-organised, methodical and self-motivated
Previous experience in a similar role would be considered favourably.
Understanding of field phenotyping
Experience in handling and analysing scientific data
Proficient in Machine learning network
Experience in SQL
Experience in software design
In addition, the following mandatory requirements apply:
Work Rights: You must have unrestricted work rights in Australia for the duration of this appointment to apply. Visa sponsorship is not available for this appointment.
Questions?
For more information about this opportunity, please contact Daniel Smith at [email protected] . For application queries, please contact [email protected] stating the job reference number (below) in the subject line.
Want to Apply?
All applicants must upload the following documents in order for your application to be considered:
Cover letter addressing the ‘About You’ section
Resume
Other Information
At UQ we know that our greatest strengths come from our diverse mix of colleagues, this is reflected in our ongoing commitment to creating an environment focused on equity, diversity and inclusion . We ensure that we are always attracting, retaining and promoting colleagues who are representative of the diversity in the broader community, whether that be gender identity , LGBTQIA+ , cultural and/or linguistic , Aboriginal and/or Torres Strait Islander peoples , or people with a disability . Accessibility requirements and/or adjustments can be directed to [email protected] .
If you are a current employee (including casual staff and HDR scholars) or hold an unpaid/affiliate appointment, please login to your staff Workday account and visit the internal careers board to apply for this opportunity. Please do NOT apply via the external job board.
Applications close April 17th 2024 at 11.00pm AEST (Job Reference Number - R-37536). Please note that interviews have been tentatively scheduled for the week commencing April 22nd 2024.
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