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using languages such as Python, R, and Bash. · Experience developing, implementing, and optimizing computational pipelines and bioinformatics tools for large-scale genomic datasets. · Strong
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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of optimizing pipelines for large-scale genomic projects. Special Instructions Required documents: CV Research summary of PhD work. Cover letter describing your interest in the lab and initial ideas for new
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such as system usability, improved patient outcomes, and workflow optimization. Preference will be given to candidates who have completed a clinical informatics fellowship or similar advanced degree