Part-time (21 hours per week), until 31 December 2027, based at the Sydney Eye Hospital Centre Block
Advance cutting-edge multiple sclerosis research by applying your neuroimaging expertise within a collaborative and globally recognised research environment at the Save Sight Institute
Base Salary $103,185 - $111,237 (pro-rata) + 17% superannuation
About the opportunity
Join the Save Sight Institute at the University of Sydney as a Clinical Image Analyst and contribute to innovative neuroimaging research focused on advancing understanding of multiple sclerosis pathology, progression, and imaging biomarker development.
We are seeking a highly experienced MRI Lesion Segmentation Analyst to perform detailed manual lesion segmentation and quality-controlled lesion mask generation for large-scale multiple sclerosis imaging studies and emulated clinical trial datasets. This role requires extensive expertise in the identification and delineation of MS pathology on brain MRI, including a deep understanding of neuroanatomy, white matter lesion characteristics, and MRI appearance of chronic MS lesions across longitudinal studies. The successful candidate must have advanced experience using JIM software (Xinapse Systems), with a minimum of several years’ experience in MS lesion segmentation using this platform specifically.
Reporting under broad supervision, you will apply your technical judgement and attention to detail to perform complex image analysis activities, manage imaging datasets, and contribute to the continuous improvement of neuroimaging workflows and methodologies. You will also play an important role in supporting research outputs, including publications, presentations, and grant-related activities, within a collaborative and research-intensive environment.
Your key responsibilities will be to:
Generation and refinement of high-precision lesion masks from longitudinal MRI datasets, rigorous quality control, and independent handling of complex lesion analysis workflows used in clinical research studies
The role requires exceptional attention to detail, consistency, and the ability to work independently within a specialised neuroimaging research environment where lesion segmentation accuracy is critical for downstream biomarker analysis and clinical trial emulation studies.
Perform manual and semi-automated lesion segmentation and masking of MRI brain scans, including T1-weighted, T2-weighted, and FLAIR sequences, to support high-quality neuroimaging research outcomes.
Assess MRI datasets for image quality, protocol adherence, and suitability for analysis, ensuring accurate and reproducible imaging-derived data.
Conduct longitudinal review of serial MRI studies to identify lesion progression and radiological change over time within the MAD-MS study.
Organise, maintain, and archive imaging datasets, lesion masks, and associated documentation in accordance with study protocols and research governance requirements.
Apply quality assurance processes and standard operating procedures to maintain consistency, integrity, and reproducibility across imaging analysis workflows.
Collaborate with investigators, clinicians, and research staff to provide technical imaging expertise and contribute to publications, presentations, and grant submissions.
About you
Relevant tertiary qualifications in medical imaging, neuroscience, biomedical science, or a related discipline, with demonstrated experience in MRI image analysis and lesion segmentation.
Strong knowledge of neuroanatomy and the radiological manifestations of neurological disease, with the ability to apply specialised technical expertise within established research protocols.
Exceptional attention to detail and analytical capability, with experience performing accurate and reproducible technical image analysis and quality assurance activities.
Well-developed organisational skills with the ability to manage imaging datasets, documentation, and competing priorities in a research environment.
Experience working within neuroimaging research environments, ideally involving multiple sclerosis or neurological disease research, with exposure to specialised neuroimaging software platforms for image segmentation and analysis.
Sponsorship / work rights for Australia
You must have unrestricted work rights in Australia for the duration of this employment to be eligible to apply. Visa sponsorship is not available for this appointment.
Pre-employment checks and declarations
Your employment is conditional upon the successful completion of all pre-employment or background checks required for the role in terms satisfactory to the University. Also, to meet the University’s obligations under the National Higher Education Code to Prevent and Eliminate Gender-Based Violence you will be asked to declare if you have been investigated for, or found to engaged in, sexual harm or gender-based violence in the course of previous employment or in a legal process. 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.
EEO statement
At the University of Sydney, our shared values are trust, accountability and excellence and we strive to be a place where everyone can thrive. We are committed to creating a University community that thrives through diversity and reflects the wider community that we serve. We deliver on this through our commitment to diversity and inclusion , evidenced by our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People , women , people living with a disability , people from culturally and linguistically diverse backgrounds , and those who identify as LGBTQIA+ . We welcome applications from candidates from all backgrounds.
We are proud to be recognised as an Australian Workplace Equality Index (AWEI) Platinum Employer. Find out more about our work on diversity and inclusion .
How to apply
Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the Apply button at the top of the page.
For employees of the University or contingent workers, please login into your Workday account and navigate to the Career icon on your Dashboard. Click on USYD Find Jobs and apply.
For a confidential discussion about the role, or if you require reasonable adjustment or any documents in alternate formats, please contact Roshik Prasad, Recruitment Operations by email to [email protected]
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Applications Close
Thursday 11 June 2026 11:59 PM
