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will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
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of degree equivalency. Preferred Qualifications: Background in medical imaging, imaging simulation, and machine learning. Programming in Python, MATLAB, C, CUDA. Other Requirements: This position is hybrid
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., M.D., D.V.M.) Preferred Qualifications:. Detail-oriented, very well organized, and approach laboratory procedures with critical thinking. Strong initiative and eagerness to learn. Outstanding problem
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focuses on advanced methodologies in abdominal imaging, particularly applications of machine learning and deep learning to medical image analysis. The lab aims to advance existing imaging techniques and
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· Willingness to learn mouse protocols for cancer research. · Qualifying competencies include excellent oral and written communication skills. · Excellent self-motivation, organizational skills, creativity
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experimental design. Collaborate with another postdoc in the NIH Center to use scientific machine learning (SciML) to automatically select mathematical models from data. Minimum Requirements: Ph.D. in applied