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, Engineering, Physics, Medical Physics, Applied Math, Statistics, or a related field. * Strong background in deep learning (e.g., CNNs, transformers) and familiarity with emerging techniques for reasoning and
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genomic, epigenomic, and fragmentomic data, from patient liquid biopsy samples Design and evaluate deep learning models for MRD detection and characterization Collaborate with multidisciplinary teams across
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reporting standards * Familiarity with deep learning technologies (e.g., CNNs, transformers) * Experience with Python and ML ecosystem skills (e.g., PyTorch, scikit-learn, etc.). * Skilled in writing and able
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development through emerging deep learning techniques is of strong interest. The candidate will also evaluate and integrate existing tools and databases into high-throughput pipelines, and facilitate
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& Responsibilities: Develop advanced deep learning methods for radiology or pathology medical imaging Integrate imaging data with EHR, clinical notes, or genomic data Conduct research on segmentation, classification
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, providing them with a deep understanding of the field and hands-on experience in informatics research. In addition to the primary informatics and research responsibilities, there is the potential