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analysis; Biomarker identification through the use of machine learning approaches; and Multi-omics data integration with genomics, transcriptomics and methylomics data. Job Description Primary Duties
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interpreting wet-lab synthesis data are encouraged to apply and will have opportunities to explore machine learning-guided approaches in chemistry. In addition to excellent research skills, we are seeking
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activities and psychological stress. Duties/Responsibilities The researchers will contribute specifically through: Gathering data, developing and implementing machine learning models, and interpreting findings
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. Experience with high-throughput molecular biology assays. Experience with complex functional experiments. Background in machine learning, AI, or data integration for genomic datasets. Familiarity with gene
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to study alveolar barrier function, tissue inflammation and matrix remodeling events. This post will provide the opportunity to acquire cutting-edge immunology, genomics, and single cell RNA-seq techniques
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in adaptive immune systems (e.g., co-evolution of bacteria and phages, as well as T and B cells with pathogens). • Physics-informed machine learning of biophysical systems (e.g., developing optimal
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techniques, applying computational neuroimaging, machine learning and fluid dynamics methodologies to interpret these complex datasets. They will work closely with a dynamic team comprised of neurosurgeons
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Position Summary The DRIVES Project is seeking a Postdoctoral Research Associate with interests in Alzheimer’s disease (AD), biomarkers, driving, machine learning, and/or geographic information