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, performing data collection and processing of cryo-EM data. Setup of future hardware and software as the research technology is upgraded. Providing lab members support in data collection, image processing, map
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directly with the PI on applying interdisciplinary neuroscience and electrophysiology techniques toward studying the nervous system of the heart. Qualifications: Education 5 years or less from a PhD or MD
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laboratory notebooks. Monitor progress of research projects and coordinate with Principal Investigator and Program team to stay on budget and schedule to meet the milestones and deliverables. Follow standards
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pain), with a focus on with a focus on ion channels, neural circuits, and neuromodulation. Candidate must have completed the requirements for the PhD degree or equivalent in Neuroscience related fields
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directly with the PI on applying interdisciplinary neuroscience and electrophysiology techniques toward studying the nervous system of the heart. Qualifications: Education 5 years or less from a PhD or MD
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to therapies and vaccines against human diseases. We are a team of highly interactive investigators that have expertise in immunology, molecular biology, virology, microbiology, structural biology, computational
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. The Ur-BIOME Research Program at Duke University, led by Dr. Nazema Siddiqui in the Department of Obstetrics and Gynecology’s Division of Urogynecology, is seeking a highly motivated Postdoctoral Fellow
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research training program, unless research training under the supervision of a senior mentor is a primary purpose of the appointment. · The appointee works under the supervision of a scholar or a department
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program. A doctoral degree or equivalent (Ph.D., ScD., DrPH, M.D., D.V.M., DDS etc) in Epidemiology, Biostatistics/Statistics, Bioinformatics, Genomics, or other relevant disciplines. Knowledge in the areas
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, computer science, bioinformatics, or o ther related disciplines is required. Strong interest, research background and experience in the methodology research in functional data analysi s, tensorregression, high