13 parallel-computing-numerical-methods PhD positions at Duke University in United States
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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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, 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
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degree in biological or medical sciences or another field using quantitative methods. Experience deriving meaningful hypotheses or insights from large datasets, as evidenced by first-authored publications
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(Harward et al., Nature 2016; Hedrick et al., Nature 2016; Krishnamurthy et al., Ann Neurol 2019). We are particularly interested in developing focused ultrasound as a new method for non-invasively
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, methods will include video- and machine-learning supported behavioral studies in mice, mouse genetics, fluorescent imaging, electrophysiology, pharmacological studies of irritant and thermosensory receptors
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, biochemistry, and molecular biology. • Familiarity with various analytical methods and electrophysiology is desirable. • Previous research experience in the field of anesthesiology will be an asset. Required
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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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, innovative technologies. There are also numerous opportunities to launch creative, new research directions through internal grant mechanisms, such as those supported by the Duke Institute for Brain Sciences
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be considered, strong preference will be given to those with experience in analytical chemistry, mass spectrometry, quantitative proteomics and/or computational biology. This position offers a vibrant
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Investigator and Program team to stay on budget and schedule to meet the milestones and deliverables. Follow standards of responsible conduct in research. Comply with good scholarly and research practices