Staff Data Scientist - Medical Imaging

REQUIRED:

• ability to learn
• problem solving
• Extensive experience with various medical imaging techniques such as MRI, CT, X-ray, ultrasound, PET/CT
• Experience with medical imaging software and tools for image acquisition, processing, and analysis
• Experience in applying machine learning techniques to medical image analysis tasks
• Knowledge of deep learning architectures commonly used in medical imaging (e.g., CNNs for image classification, segmentation)
• Ability to develop and implement algorithms for medical image analysis
• Understanding of DICOM standards and medical imaging file formats
• Experience in curating, managing, analyzing, and interpreting biomedical images
• Proficiency in image segmentation, registration, and feature extraction techniques
• Familiarity with image visualization tools and advanced visualization software
• Knowledge of image enhancement and artifact compensation methods
• Familiarity with medical terminology and clinical workflows
• Experience in quantitative image analysis techniques, including feature extraction, segmentation, registration, and classification
• Experience in researching and experimenting with new techniques for medical image analysis

• Ability to prototype new algorithms and methods for visualization and management of medical imaging data

  SUGGESTED:

• 6+ years of medical imaging data analysis experience
• 6+ years of deep learning and machine learning application experience
  • Comprehensive knowledge of anatomy as visible in medical images
  • Advanced knowledge of 3D image reconstruction and multidimensional data integration
  • Mastery of programming languages used in medical imaging analysis and ability to optimize code for performance and scalability
  • Expertise in handling large-scale medical imaging datasets and developing data pipelines for efficient processing
  • Proficiency in image segmentation, registration, and feature extraction techniques
  • Experience with medical imaging software and tools for image acquisition, processing, and analysis
  • Extensive experience in developing and implementing cutting-edge deep learning algorithms for medical image analysis, including CNNs, RNNs, and hybrid methods
  • Proficiency in advanced machine learning techniques, including self-supervised and weakly-supervised learning approaches