About the Role
We're looking for an MRI Application Specialist with strong expertise in anatomy, pathology interpretation, and hands-on segmentation. You will support MRI data curation, segmentation workflows, collaborate closely with radiologists and AI engineers, and help build products aligned with upcoming healthcare technologies.
Key Responsibilities
- Perform manual and semi-automatic segmentation of all anatomies, especially MSK, including joints, bones, cartilage, ligaments, tendons, and soft tissues.
- Review and interpret multi-sequence MRI datasets (T1, T2, PD, STIR, GRE, fat-sat, etc.).
- Support MRI protocol understanding, quality checks, and dataset preparation.
- Contribute to annotation guidelines, workflow improvement, and tool enhancement.
- Document segmentation protocols and maintain accurate records of anatomical variations.
Skills
· Strong knowledge of anatomy across all major MRI sequences.
· Knowledge of relevant anatomical structures and pathologies across various MRI sequences.
· High precision in 2D and 3D segmentation.
· Proficiency with segmentation tools such as 3D Slicer, ITK-SNAP, Mimics, MITK, Horos, or equivalent.
· Ability to work with DICOM data and MRI-specific parameters.
· Strong visual reasoning and attention to detail.
· Ability to manage datasets and maintain consistency across volumes and sequences.
Requirements
- Strong understanding of MRI imaging principles, contrast mechanisms, and sequence interpretation.
- Ability to follow structured segmentation protocols with high accuracy.
- Clear communication skills for discussions with radiologists and technical teams.
- Comfortable handling large MSK MRI datasets and various imaging artefacts.
Education
- Bachelor's degree in Radiology, Medical Imaging, Biomedical Engineering, or a related field is a MUST.
Experience
- 2–5 years of experience working with MRI datasets and performing segmentation.
- Experience in medical imaging annotation projects or clinical imaging workflows.
- Prior exposure to AI/ML imaging teams is a plus.