17 phd-rehabilitation-engineering-computer-science PhD positions at Duke University in United States
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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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students) or residents or fellows at various levels Qualification: · Ph.D. in neuroscience or neurobiology or rehabilitation science or Biomedical Engineering, or a related field. MD with additional human
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and highly interactive academic setting in a new state-of-the-art research facility, along with NIH-sponsored funding, access to outstanding resources and technology platforms, strong computational
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. Candidates with background knowledge and hands-on experience in mouse models, proteomics, 3D organoids, primary cell purification, and culture skills are particularly welcome. Requirements: A PhD or MD/PhD
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, the successful candidate is expected to design and perform experiments to identify pathological mechanisms underlying craniofacial pain (e.g. temporomandibular disorders pain, migraine, and eye pain
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on applying cutting-edge neuroscience techniques toward studying the nervous system of the heart. Qualifications: Education 5 years or less from a PhD or MD/PhD Degree with a background in cardiac biology
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will perform the following tasks: • Design, implement, and maintain scalable computational pipelines for multi-omics data, including bulk/single-cell RNA-seq, spatial transcriptomics, metagenomics
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. The Bagnat lab in the Cell Biology department seeks to hire a postdoctoral associate to conduct experimental research in the field of morphogenesis and physiology using zebrafish as model system. Candidates
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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