Job Description

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 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