Research Assistant

• Part Time 6 month fixed term opportunity for a Research Assistant
• Join a high-performing, multidisciplinary Computational Neuroimaging team dedicated to the ongoing development of novel imaging biomarkers for Multiple Sclerosis
• Base Salary HE04 $83,038 or HE05 $89,755 + 17% superannuation, based on experience

About the opportunity

Multiple Sclerosis (MS) affects more than 2.9 million people worldwide and is the leading non-traumatic cause of neurological disability in young adults. In Multiple Sclerosis, not all white-matter lesions are equal — some contribute disproportionately to long-term disability while others remain clinically silent. We hypothesis that a subset of MS lesions, jointly characterised by their degree of axonal loss and anatomical location, can substantially improve prediction of clinical progression. The project is aiming to develop a novel lesion classification framework that using routinely acquired clinical MRI.

You will join a high-performing, multidisciplinary Computational Neuroimaging team dedicated to the ongoing development of novel imaging biomarkers for Multiple Sclerosis, bridging the gap between advanced computational methods and real-world clinical impact. The team operates in a leading-edge environment that sits at the intersection of medical imaging, data science, and clinical neurology. We are committed to the clinical translation of imaging metrics, with a specific focus on improving the lives of individuals with Multiple Sclerosis (MS).

You will be joining our multidisciplinary team, contribute to the ongoing development of novel imaging biomarkers for multiple sclerosis.

Your key responsibilities will be to:

• neuroimaging Pipeline Management: implement and maintain automated MRI preprocessing and analysis pipelines for large-scale, multi-site clinical datasets.

• advanced Lesion Analysis: Implement lesion segmentation and characterisation techniques using structural, diffusion, and quantitative MRI.

• data Management: Oversee the curation and quality control of the training and validation dataset

• machine Learning Development (HEO5): implement model training to classify lesion severity and map anatomical connectivity. Build and validate predictive models to establish the relationship between imaging metrics and longitudinal clinical disability.

About you

Essential:

• academic Qualifications: Bachelor's in biomedical engineering, Computer Science, Medical Image Analysis, Applied Statistics, or a related quantitative discipline. (Current enrolled HDR students are also encouraged to apply)

• imaging Expertise: Demonstrated experience in MRI quantitative analysis, experience with structural diffusion-weighted (dMRI) is preferable (HEO5)

• software Proficiency: Expert command of industry-standard neuroimaging toolkits (e.g., FSL, FreeSurfer, ANTs, MRtrix3)

• data Handling: Proven ability to manage, curate, and perform quality control on large-scale, multi-site neuroimaging datasets

• programming Proficiency: Proficiency in Python, including the ability to automate pipelines and manage version control (Git) and data science libraries

• scientific Communication: Demonstrated ability to draft high-quality technical reports and manuscripts for peer-reviewed journals

• problem Solving: A proactive approach to troubleshooting complex computational pipelines and data inconsistencies

• collaborative Mindset: Experience working within multidisciplinary teams, specifically the ability to communicate technical concepts to non-technical clinical stakeholders (Neurologists/Radiologists)

• time Management: Ability to work independently and meet project milestones within a fast-paced research environment

Desirable:

• deep Learning: Experience with frameworks such as PyTorch or TensorFlow applied to medical image analysis

• AI Analytic Foundations (HEO5): Solid understanding of machine learning principles and high-level statistical modelling for predictive analytics.

• Translational Interest: A genuine interest in clinical biomarker validation and the desire to see research outputs impact patient care.

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

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 Danielle Selinger Recruitment Consultant by email to [email protected]
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