Data Scientist - Medical Imaging and Computer Vision

At nFerence Labs, the "Google of Biomedicine" (See also nference.ai/news for more information on our research work especially pertaining to Covid19), we are building the world's first massive-scale platform for pharmaco-biomedical computing. Our platform is premised on using AI/Deep Learning (on clinical text, medical images, and other signals) and massive high-performance computing to help pharma companies perform faster and more efficient drug discovery, and also help early diagnosis of several key diseases. We collaborate heavily with premier medical institutions such as the Mayo Clinic and build systems to get deep medical insights from patient information including patient notes and lab information, medical images, ECGs, etc. We are a well-funded company and are looking to grow on all fronts. Our team is a blend of CS folks and domain experts (biological science and medical MDs, PhDs, etc) constituting a unique community built of alumni from the likes of MIT, Harvard, the IITs, IISc, and other premier institutions. We are seeking a highly skilled Data Scientist with a strong background in medical imaging and computer vision. You will be responsible for designing, developing, and deploying intelligent image analysis systems, with a focus on object detection, optical character recognition (OCR), entity detection, and de-identification. Your work will directly impact healthcare diagnostics, automation, and research innovation. Key Responsibilities: - Develop, train, and deploy computer vision models for medical imaging applications (e.g., disease detection, image classification, segmentation). - Design and implement imaging algorithms for entity detection (e.g., identifying sensitive information) and de-identification (e.g., removing patient identifiers from images). - Build and optimize object detection and OCR systems for medical data analysis and information extraction. - Work with DICOM images, PACS systems, and medical datasets for model training, validation, and deployment. - Create scalable pipelines using Docker for containerized model deployment and reproducibility. - Collaborate with radiologists, clinicians, and research scientists to translate clinical needs into technical solutions. - Perform data preprocessing, augmentation, and annotation to enhance dataset quality. - Research and implement new algorithms to advance the field of medical image analysis. - Monitor model performance, conduct error analysis, and fine-tune models to meet stringent clinical accuracy requirements. - Write clean, efficient, and well-documented code adhering to best practices.

At nFerence Labs, the "Google of Biomedicine" (See also nference.ai/news for more information on our research work especially pertaining to Covid19), we are building the world's first massive-scale platform for pharmaco-biomedical computing. Our platform is premised on using AI/Deep Learning (on clinical text, medical images, and other signals) and massive high-performance computing to help pharma companies perform faster and more efficient drug discovery, and also help early diagnosis of several key diseases. We collaborate heavily with premier medical institutions such as the Mayo Clinic and build systems to get deep medical insights from patient information including patient notes and lab information, medical images, ECGs, etc. We are a well-funded company and are looking to grow on all fronts. Our team is a blend of CS folks and domain experts (biological science and medical MDs, PhDs, etc) constituting a unique community built of alumni from the likes of MIT, Harvard, the IITs, IISc, and other premier institutions.