77 genetic-algorithm Postdoctoral positions at Duke University in Ireland-University-Ranking-2024
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evaluation of machine learning, computer vision, and other algorithms, primarily in the context of health. They will be part of the thriving research community of Duke Spark (spark.duke.edu) where AI
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simulations and data analysis. This includes data analysis using Python-based algorithms. Experience with EELS is preferred. Skills This See Experience
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experience in simulating/implementing quantum algorithms for field theories on quantum hardware. Appointment Detail: This post‑doctoral position is a full‑time, 12‑month appointment with annual renewal
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biomarkers with clinical, genetic, and cognitive datasets. Support statistical analyses and exploratory research initiatives. Generate tables, figures, and analytical summaries for publications and
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Lab’s recent studies on gene regulation, stem cell biology, genome organization, and tissue regeneration have been published in leading journals, including Molecular Cell 2022, Nature Genetics 2023
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an interdisciplinary team of biologists and mathematicians including: Dr. Kevin Flores (Mathematics, North Carolina State University) Dr. Micah Luftig (Molecular Genetics & Microbiology, Duke University) Dr. Cliburn
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while contributing effectively within a collaborative research team. Preferred Qualifications Research experience related to vision science, neuroscience, cell biology, genetics, or retinal disease
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, genetic information, national origin, race, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status. Duke aspires to create a community built on
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Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national
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the cellular crosstalk and basic molecular mechanisms during lung repair and disease. We utilize in vivo mouse genetics, live -imaging, 3D organoids, functional screening, and next generation sequencing