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Research Fellow - Diagnostic Imaging Felix Lab at InsideHigherEd
InsideHigherEd
Baltimore, Maryland
Healthcare
Posted 0 days ago
Job Description
General Description The Johns Hopkins University School of Medicine Department of Radiology in the Russell H. Morgan Department of Radiology and Radiological Science in Baltimore, MD is seeking a post-doc research fellow to be hired in the FELIX 2.0 laboratory ( https://thefelixlab.jhmi.edu/ ). This is a full time, post-doc position. We offer a competitive salary, vacation and excellent benefits. The FELIX 2.0 laboratory aims to change the trajectory of how pancreatic cancer is detected, how patients are evaluated, and improve outcomes. Its mission is to harness the power of artificial intelligence, help radiologists and clinicians in detecting pancreatic cancer when it could have otherwise been missed. This is an innovative way of approaching what has been a challenge for many decades. Between Johns Hopkins Medicine, the Lustgarten Foundation, and Microsoft AI for Good, the FELIX 2.0 laboratory is pooling vast resources to improve how we do things, especially considering recent advancements in AI technology. The position will include developing radiomics and deep learning models from contrast-enhanced computed tomography images to improve the early detection of pancreatic tumors and improve patient management. Different machine-learning approaches will be compared, and models validated on data prospectively collected. The position will include working with internal and external databases. The candidate will contribute to coordinating expert interpretation and manuscript writing under supervision. Specific Duties/Responsibilities: Data Curation: Collect and organize datasets along with relevant clinical information to support and drive research studies Radiomics Pipeline Development: Design and optimize robust radiomics pipelines for characterization of CT images. Machine and Deep learning: Develop and implement machine learning and deep learning algorithms to built detection and prediction models for CT images Performance Evaluation: Conduct rigorous statistical analyses to benchmark and compare the performance of diverse approaches. Model Assessment and Deployment: Evaluate model limitations and implement new approaches for deploying models, enhancing their generalizability and real-world applicability. Communication and Reporting: Prepare reports and study findings to present to PI. Manuscript Preparation: Author high-quality research manuscripts for publication in peer-reviewed journals. Special knowledge, skills two (2) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre-employment physical exam except for those employees who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office.
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