16 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr"-"UCL" Postdoctoral positions at Nature Careers in United States
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of high-dimensional single-cell data, the lab aims to reconstruct accurate cell-lineage trees and use them as a scaffold to map genome-wide regulatory dynamics across development. The lab is highly
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Postdoctoral Research Associate - Hybrid Computational-Experimental Scientist in Bacterial Drug Resp
-or vice versa-who wants to grow into a scientific leader at the interface of data and biology. What You Will Do • Combine experimental and computational approaches to analyze bacterial responses
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transcriptomic data. • Detect and interpret structural variation from Nanopore/PacBio sequencing. • Build scalable, reproducible pipelines for large genome collections and public databases. • Collaborate closely
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Job Description Collaborates with new and existing program partners to support research initiatives, including the collection, analysis, and interpretation of primary and secondary data to address
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engineering, analytical chemistry, and computational methods for analyzing sequence information and molecular structures is required to perform research tasks A background in food science or food technology is
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the following document(s): A letter of motivation describing your interests, experience and motivation to join the team A curriculum vitae including a list of publications Contact information for two references
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links to representative publications on PubMed) Summary of your current research and key accomplishments Names and contact information of three references We welcome applicants from diverse backgrounds
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to applicants who have received their Ph.D. degrees in neuroscience or related fields within the last 3 years and have experience in imaging in vivo. Skills in computational neuroscience and data mining using
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increasing independence over 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