13 phd-studenship-in-computer-vision-and-machine-learning PhD positions at Duke University
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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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-TEM. · The Department of Biochemistry provides a rich intellectual environment, with research in structural biology (cryo-EM, X-ray crystallography, NMR spectroscopy), and computational biology
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experiments. Data & Analysis: • Collaborate with data scientists to analyze host and microbial data using statistical, bioinformatic, or machine learning approaches. • Contribute to the integration of spatial
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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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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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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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-dimensional variable selection, longitudinal and survival analysis, machine/deep learning, bioinformatics methods in -omics data are preferred. Demonstrated evidence of excellent programmin g, collaboration
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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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. 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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orientation or military status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends onthe robust exchange of ideas—an exchange that