The Research Fellow (Grade 1) will work with a team of researchers on the NHMRC Project “Unmasking HIV latency through disruption of HIV synapses”. The primary purpose of this position is to develop highly automated live cell image analysis pipeline to reveal the spatial-temporal dynamics of Ca2+-HIV synapse biology.
The appointee will be given the opportunity to:
- Collaborate with cell biologist at the Institute for Glycomics, Griffith University, that study HIV replication.
- Work on live-cell imaging using state-of-the-art high-speed microscopy for 4D analyses.
Key responsibilities for this position will include, but are not limited to:
- Conduct research that contributes to the development of an AI-enabled live cell image analysis pipeline for the NHMRC project.
- Develop an excellent publication record in high impact, international, esteemed peer-reviewed journals and conferences, and to seek competitive funding.
- Manage the preparation and formulation of publications, presentations and research reports arising from the research.
- Assist in mentoring and supervision of higher degree research candidates.
- Coordinate meetings between researchers and participating external participants as required.
This is a fixed term (until 31 December 2026), full time position and will be primarily based at the Griffith University Gold Coast campus. As Griffith is a multi-campus University you may be required to work across other campus locations.
Griffith University’s campuses are located on the lands of the Yugarabul, Yuggera, Jagera, Turrbal, Yugambeh and Kombumerri peoples.
Salary Range
The full time equivalent base salary will be Research Fellow, Grade 1 range $84,830 - $99,367 per annum + 17% superannuation. The total FTE package will be in the range $99,251 - $116,259 per annum.
What matters most is your drive to create a brighter future that benefits all. Through our core principles of excellence, ethics and engagement, you’ll thrive on seeing the direct and lasting impact you’ll have on every community and every future.
You will also have:
- A PhD or equivalent qualifications/work experience in Computer Science, Engineering, or Applied Mathematics.
- Solid research experience in developing AI-enabled computer vision system for non-rigid object segmentation and tracking. Experience in cell image analysis is highly desirable.
- Demonstrated publication record in high quality peer-reviewed journals and/or conferences in computer vision and machine learning.
- Excellent collaboration skills in cross functional teams with the ability to communicate to both technical and non-technical audiences.
- A demonstrated ability to work independently to meet competing deadlines, as well as to work effectively as a member of interdisciplinary teams and communicate effectively with a range of stakeholders.
