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background in molecular biology and cell biology. Experience working with animal models. Demonstrated scientific curiosity, initiative, and commitment to research excellence. Ability to work independently
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. or equivalent doctorate (e.g. Sc.D., M.D., D.V.M.) Preferred Qualifications:. A PhD or MD/PhD (or equivalent) in biological sciences Strong research background in cell biology, molecular biology, mouse models
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to understanding the fundamental mechanisms that drive cancer development, treatment response, and therapeutic resistance. By combining cutting-edge molecular biology, functional genomics, and translational research
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cancer models and patient-centered translational approaches to define mechanisms that regulate treatment response, immune evasion, and disease progression. Candidates with experience in cancer biology
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. Postdoctoral Associate Positions in Regeneration Genomics Diao Lab, Duke University School of Medicine The Diao Lab in the Department of Cell Biology at Duke University School of Medicine has multiple openings
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. Postdoctoral Associate – Oliver Laboratory The Laboratory of Dr. Trudy G. Oliver, Professor in the Department of Pharmacology and Cancer Biology and member of the Duke Cancer Institute at Duke University, is
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processes. Ongoing projects combine molecular biology, neurobiology, biochemistry, and computational approaches to address fundamental questions in RNA regulation. Minimum Requirements: Min Degree
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Qualifications:. PhD in one of these fields: Computer Science, Data Science, Biomedical Informatics, Computational Biology, Information Science or a related field. Experience in at least one of the following
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. What You'll Bring Required Qualifications Postdoctoral Associate PhD, MD, or equivalent doctoral degree in Neuroscience, Physiology, Pharmacology, Biomedical Engineering, Cell Biology, or a closely
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related fields.MD/PhD with molecular biology research experience. Experience/Training: Must have experience with analyzing omics data. Familiarity or direct experience with analysis of 10x Genomics data