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The Associate in Research will be responsible for using and developing computational algorithms to analyze single-cell and spatial-omics datasets. Specifically, we have multiple projects where we are generating
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-Lab, we are committed to develop break-through PAT technologies, with novel and advanced imaging performance in terms of spatial resolutions, imaging speed, penetration depth, detection sensitivity, and
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different types of social and ecological data at various spatial scales; o Experience working in R; o Strong written, digital and verbal communication skills, able to translate complex ideas into accessible
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analysis of spatial-omics and imaging data, developing a framework for simulations, simulating epidemics on social networks, building generative models to improve computation time for simulations, and other
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in applied economic analysis (e.g., causal inference, econometrics, spatial equilibrium modeling). • Experience working with large-scale datasets and interdisciplinary research. • Demonstrated research
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, ultimately aiming to find better treatments for patients with cancer. This position is intended to provide experimental support by working in the laboratory of physician scientist Dr. Christine Eyler (https
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, providing Fellows with resources and networks to launch impactful careers. To learn more about the SCALES Postdoctoral Fellowship Program, visit our program page: https://climate.duke.edu/what-were-doing
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will develop novel machine learning and artificial intelligence (ML/AI) methods for genomics data, especially: large-scale single-cell genomics data, high-definition spatial genomics, digital pathology
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., spatial transcriptomics, single-cell transcriptomics, metagenomics), bioinformatics (including machine learning and artificial intelligence), synthetic biology, organoid technology, CRISPR, molecular