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Field
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the mentorship of Dr. Ying Wang in the Department of Biomedical Informatics, the scholar will investigate the genetic architecture of disease onset, progression, multimorbidity, and clinical outcomes using large
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including causal inference and prognostic/risk prediction modelling. It will be essential to have evidence of strong data management skills and experience managing large linked administrative datasets using
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, computational biology, genomics, or a related quantitative field. You will have strong programming skills (Python, R, Linux) and experience analysing large-scale sequencing datasets, ideally RNA-sequencing data
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learning, decision-making, belief updating) Coordinating large database of computational task data for harmonized analyses Modeling individual differences and within-person change over time in a longitudinal
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. Ongoing projects leverage large-scale multimodal clinical data, including electronic health records (EHRs), medical imaging, genomics, wearable devices, and unstructured clinical text, to develop novel
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to extract biological information from high-dimensional data Integrate proteomics data with biological (e.g. genomics) data and clinical information Collaborate closely with mass spectrometry experts
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develop a body of high-quality publications in scholarly journals with global impact Proficiency in statistical software packages, including SPSS and R, for large and complex data analysis Proven knowledge
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and deep learning methods for large-scale genomic, clinical, and imaging biobank data, with stable multi-year NIH support. The Zhi Laboratory has a sustained track record of methods development
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big data. Among the key duties of this position are the following: Participate in lab meetings, research-in-progress seminars, data analysis, and presentations at conferences. Participate in the ACTIVE
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University of California, Los Angeles | Los Angeles, California | United States | about 10 hours ago
clinical data. A major focus of the position will be identifying genomic and immunologic features associated with variation in immune responses and clinically relevant phenotypes. A Ph.D. or equivalent