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a PhD in machine learning, math, stats, physics, or some other technical area by the time the position starts. Additional Qualifications Candidates should have significant experience in some area of
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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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-accurate-portable-diagnostics/. What you’ll do: Design, fabricate, characterize, and optimize electrochemical biosensing technologies for real-time detection. Develop and implement novel surface chemistries
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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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do: Design, fabricate, characterize, and optimize electrochemical biosensing technologies for real-time detection. Develop and implement novel surface chemistries to improve sensor performance
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data Clear scientific writing and communication; a track record of publications Experience with causal inference Bonus: experience with explainable ML, optimization/decision strategies, or work with EHR