AI Data Scientist

Job Description

Programming Languages: Proficiency in Python for developing and implementing AI models Deep Learning Frameworks: Expertise in TensorFlow, PyTorch, or Keras for building and training CNNs Image Processing Libraries: Familiarity with OpenCV, scikit-image, and PIL for handling medical images Big Data Technologies: Experience with Hadoop, Spark, and SQL for managing large datasets Domain Knowledge Medical Imaging: In-depth understanding of X-ray imaging techniques and interpretation Convolutional Neural Networks: Extensive knowledge of CNN architectures and their applications in image analysis Computer Vision: Strong background in image processing, segmentation, and feature extraction Radiology: Familiarity with common pathologies detectable in chest X-rays, such as pneumonia and pulmonary nodules Role & responsibilities - Develop and implement CNN models for automated detection and classification of abnormalities in chest X-rays - Design and optimize deep learning algorithms for image segmentation, classification, and reconstruction - Collaborate with radiologists and medical professionals to improve model accuracy and clinical relevance - Evaluate and enhance model performance using various metrics and validation techniques Projects and Achievements - Successfully implemented a CNN-based model for pneumonia detection in chest X-rays with high sensitivity and specificity - Developed a deep learning framework for 3D visualization of X-ray data, significantly reducing processing time - Contributed to the creation of computer-aided diagnosis (CAD) systems for pathology image analysis - Implemented data augmentation techniques to improve model generalization across diverse patient populations Preferred candidate profile - Ph.D. or Master's degree in Computer Science, Data Science, or a related field - Certifications in deep learning, such as Deep Learning Specialization from Coursera or similar programs - Continuous learning through workshops, conferences, and online courses in AI and medical imaging In addition, the individual is expected to stay updated with the latest advancements in AI and deep learning for medical image analysis