Staff Data Scientist

17 hours ago

Bengaluru Karnataka, India ConcertAI Full time

**Work Experience**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
- 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
- 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

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