78 parallel-computing-numerical-methods-"Prof" Postdoctoral research jobs at Nature Careers in United States
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time. Collaborate on project and analysis design guided by their PI. Develop new computational methods. Adhere to field and lab standards for data analysis. Identify, process, organize, interpret, review
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, require limited supervision and high-level of independence are highly desirable. About the lab and St. Jude: Our lab focuses on computational methods development and large-scale genomic/genetic analysis
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The successful candidate will be responsible for developing computational and systems biology approaches to analyze spatial omics data and single-cell omics data (e.g., scRNA-seq, scATAC-seq, single
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Position Overview: Join the dynamic research community at the University of California, Berkeley, as a Postdoctoral Scholar in Neuroscience, working in the laboratory of Prof. Chunlei Liu
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St. Jude is seeking outstanding candidates for postdoctoral fellowship positions in the Childhood Hematological Malignancies Training Program. This prestigious, NIH-sponsored T32 training program
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://pritykinlab.princeton.edu ) develops computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi-modal single-cell, spatial and genome editing
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. All resumes submitted by search firms to any employee or other representative at St. Jude via email, the internet or in any form and/or method without a valid written search agreement in place and
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understanding of geomagnetic field evolution across different timescales, including both stable and extreme periods. This will involve working with data-based models and numerical dynamo simulations
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given to applicants who have received their Ph.D. degrees in behavioral neuroscience or related fields within the last 3 years and have experience in computational neuroscience and data mining using
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We invite applications for a NIH-funded postdoctoral researcher position in our computational lab at UMass Chan Medical School. We develop methods to reconstruct multi-modal, condition-dependent