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identify the cells, cellular states, and biological programs through which genetic variation influences disease. Your work will sit at the intersection of statistical genetics, machine learning, and
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an outstanding environment in which to develop machine learning tools and engage with an interdisciplinary community of researchers with an interest in AI for healthcare. The post holder will have opportunities
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leading experts in autism research, computer vision, machine learning, psychiatry, and developmental science to develop innovative technologies that improve how caregiver-child interactions and
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discoveries made in the laboratory with meaningful improvements in patient care. You will be part of a research environment that values curiosity, creativity, scientific rigor, and continuous learning while
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analysis, and data visualization. Apply advanced statistical, machine learning and AI methods when appropriate. Review analysis outputs and ensure methodological consistency and quality. Collaborate with
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University of California, Los Angeles | Los Angeles, California | United States | about 23 hours ago
association studies, single-cell RNA-seq/other single-cell omics, machine learning applied to biomedical data, multimodal or multi-omics data integration, high-dimensional immunology datasets, development
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Bayesian inference, likelihood-free inference, uncertainty quantification, identifiability analysis, or scientific machine learning. Strong programming skills (Python, Julia, Matlab, C++, or similar). Strong
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academic health center, Rutgers Biomedical and Health Sciences (RBHS) takes an integrated approach to educating students, providing clinical care, and conducting research, all with the goal of improving
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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working towards a shared goal. You will be responsible for the design and pilot testing of machine learning-based automated ultrasound video analysis models that incorporate temporal reasoning. The research