Job Title

Job Summary: We are seeking qualified radiologists or medical imaging specialists to support a large-scale neuroimaging annotation project.The goal is to deliver pixel-wise segmentation of 52 distinct brain sub-regions from MRI DICOM scans, following clinical standards with high anatomical precision. The annotated dataset will support advanced clinical research and development in neuroanatomy.Key Responsibilities: Perform high-accuracy pixel-wise segmentation of MRI brain images. Annotate and label 52 medically defined anatomical brain sub-regions per slice. Adhere to clinical SOPs, structural boundaries, and reference guidelines provided. Review and approve annotations (as a Radiologist reviewer) to ensure clinical accuracy. Collaborate with the quality assurance team to resolve discrepancies. Provide feedback on tools and processes to improve efficiency and accuracy. Maintain project status logs and participate in periodic QA or progress reviews.Required Qualifications: MBBS with Radiology specialization (MD/DNB/DMRD) or equivalent clinical training. Minimum 2 years of experience in brain MRI interpretation or neuro-radiology. Prior experience in medical imaging annotation is highly preferred. Strong understanding of neuroanatomy and MRI structural segmentation. Ability to follow detailed SOPs and anatomical references with precision. Familiarity with digital annotation platforms (e.g., RedBrickAI, 3D Slicer, ITK-SNAP)Preferred Skills: Clinical-level decision-making in labeling complex anatomical regions. Experience working with DICOM viewers and annotation workflows. Eye for detail and ability to identify minute neurostructural boundaries. Ability to work independently and meet strict quality and timeline targets.Project Details: Data Type:Neuro MRI DICOM scans Series Count:10 MRI series Total Slices:~3,000 (approx. 300 slices/series) Regions to Annotate:52 brain sub-regions Annotation Volume:~156,000 segmentations Tool:Preferred – RedBrickAI (training provided); alternatives may be discussed Format:Binary pixel-wise mask per slice per region Timeline:Up to 6 months from project startCompensation: Competitive per-slice or per-region compensation based on medical expertise. Flexible payment models depending on experience, accuracy, and speed. Opportunities for long-term collaboration on medical AI and imaging projects.