Medical Imaging Specialist CT

Position: Medical Imaging Specialist – CT Segmentation & Ground Truth Annotation Location: Uppsala, Sweden Employment: Fixed-term, 12 months, full-time (100%) Salary: 35,000 SEK/month Start date: By agreement

About CarcinoQuant AB

CarcinoQuant AB is a Swedish medtech company developing an automated tool for quantitative analysis of CT images in oncology. Our platform is designed to measure tumour volume and track tumour growth over time, providing clinicians and researchers with objective, reproducible metrics for monitoring cancer progression. We are building the next generation of AI-driven decision support for oncology imaging, and we are now looking for a skilled medical imaging specialist to support the development of our AI models.

About the role

You will perform expert manual segmentation of tumours in CT images, creating high-quality ground truth datasets used to train and validate CarcinoQuant's automated AI models for cancer analysis. The work requires precision, domain knowledge, and an understanding of radiological imaging in oncology. Your contributions will directly determine the quality and clinical validity of our AI system.

The role will also comprise LLM training and programming work but the primary work to be undertaken will be the aforementioned annotation work.

Responsibilities

• Manual delineation and segmentation of tumours in CT image datasets
• Quality control and review of segmentation outputs
• Contributing to the development of annotation protocols and guidelines
• Collaborating with the technical team on iterative model improvement

Requirements

• Degree in medical imaging, radiography, medical physics, or a related field
• At least two years of practical experience with CT imaging in an oncological or radiological setting
• Solid understanding of tumour morphology and radiological anatomy
• Proficiency in English (working language)
• Experience with segmentation software or medical image annotation tools
• Familiarity with AI/ML workflows in medical imaging
• Experience with DICOM data

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