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Field
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Posting Details Position Information Fiscal Year 2025-2026 Position Title Postdoctoral Associate, Microbiology and Immunology Classification Title Postdoctoral Associate Department Microbiology and
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will be responsible for spearheading the design and implementation of data analysis through open source or in-house developed pipelines, adapting and troubleshooting analytical methodology, and
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& Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty mentor including (but not limited
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Diploma/Graduation Equivalent, to the extent permitted by the JHU equivalency formula. Preferred Qualifications Technical Skills and Expected Level of Proficiency Analytical Skills-Awareness Data Entry
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disparities in supportive care medication (SCM) use, using national datasets (e.g., SEER-Medicare, SEER-MHOS), predictive analytics, and stakeholder-engaged methods. The lab is committed to actionable research
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writing and analytic skills. Experience working in legal and other historical archives. Demonstrated experience with historical data collection and analysis. Demonstrated ability in collaboration and
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analytical chemistry and with a preference to a strong background in chemistry. Candidates with practical experience in non-target analysis and data analysis workflows, gas chromatography of very volatile
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. Qualifications Ph.D. in Physics, Materials Science, or a related field. Hands-on experience with cleanroom nanofabrication. Familiarity with transport experiments (thermal, electrical) is a plus. Strong analytical
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validation; proficiency in Python and scientific computing, including experience with finite element methods, preferably using FEniCS or DOLFINx; strong analytical and communication skills, with the ability
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skills Competency in or willingness to learn process-based modelling Strong data management skills and proficiency with analytical tools e.g. Matlab, R, Python Previous experiences with eddy covariance