Part Time 6 month fixed term opportunity for a Research Assistant

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.