52 programming-"https:" "https:" "https:" "https:" "https:" "Data driven Materials Modeling" research jobs at Duke University
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may include teaching responsibilities. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless research
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behavioral data will be viewed favorably. • Applicants’ ideas about how their research program could contribute to research in the Lab will also be a plus. Position Details: This position will be in-person
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breast cancer research program focused on mechanisms of tumor progression, therapeutic resistance, and tumor-immune interactions. The successful candidate will lead experimental projects using breast
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microscopy, optogenetics, or in vivo imaging techniques. Experience with electrophysiological recording methods, including patch-clamp techniques. Programming and data analysis experience using MATLAB, Python
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academic record and thrive in a collaborative multidisciplinary research environment. The candidate should be able to, and be excited about, working in a varied lab group setting; plan and conduct
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program focused on understanding how RNA modifications regulate gene expression and cellular function in health and disease. Our laboratory investigates the molecular and biological functions of m6A
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with faculty, trainees, and multidisciplinary research teams across basic science and clinical programs to advance translational pain research. Pursue professional development and research independence
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clinical care. The position is intended to provide intensive methodological training, opportunities for scientific leadership, and support for developing an independent research program. The project centers
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for postdoctoral fellows. We are seeking highly motivated candidates to join our research program in regeneration genomics. Our laboratory develops and applies cutting-edge genomics and proteomics technologies
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foundation for an independent research trajectory. REGAL is a multidisciplinary research program integrating social epidemiology, molecular epidemiology, and global health to investigate the drivers of cancer