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and machine learning. Dr. Liu's research interests lie in modeling the rapidly-accumulating big data (e.g., muti-omics) in biology and medicine for precision medicine via a variety of statistical and
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, electrical and computer engineering, data science, informatics, biomedical engineering, or a related field. Preferred: Demonstrated expertise in AI-driven drug discovery, machine and deep learning
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) Cleaning and managing large datasets from administrative data sources or online learning platforms Causal machine learning (e.g., double/debiased machine learning (DML), causal forests, generic ML) Learning
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or similar) Preferred Qualifications: Experience with MRI/fMRI/DTI, PET, multimodal fusion, and/or machine learning Strong programming skills (Python/MATLAB), version control, and HPC workflows Special
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field. Preferred Qualifications: • Strong publication record in peer-reviewed journals or top-tier conferences relevant to machine learning, computational biology, virology, immunology, or structural
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clinical features using machine learning and foundational modeling approaches. This work supports disease modeling across chronic kidney disease, acute kidney injury, cancer, and neurological conditions. A
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of Biostatistics at University of Florida and Dr. Hongkai Ji (remote) in the Department of Biostatistics at John Hopkins University. This position, available immediately, focuses on developing statistical, machine
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computer science using data-driven techniques (graph theory, ICA, machine learning), in other imaging modalities (DTI; MEG), and in multimodal integration will be relevant. Experience with AFNI/SUMA, SPM, FSL