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Field
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fellow to investigate molecular mechanisms underlying lung infections (viral or fungal) and chronic lung diseases such as asthma. Research in the Chen lab is currently supported by multiple NIH R01 grants
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background in scientific data visualization, uncertainty quantification, AI/ML, statistics or a related field. Proficiency in Python and C++ programming languages. Excellent written and oral
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(Principal Investigator) the Postdoctoral Associate (Postdoc) will assist in multiple aspects of the lab’s research, including study design, data collection, study management, data analysis, and interpretation
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
: 277494287 Position: Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning Description: The Atmospheric and Oceanic Sciences Program at Princeton University, in
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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independently within a supportive group setting. Ensure compliance with environment, safety, health and quality program requirements Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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molecular and cellular biology, biochemistry, omics, bioinformatics, electrophysiology, behavior, and multiple microscopy techniques. The hired postdoctoral researcher will receive compensation based
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human or monkey electrophysiology. Studies will include simultaneous recordings and stimulation from multiple, interconnected brain regions. The researcher will gain experience with the use of laminar
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, is seeking highly motivated candidates for multiple postdoctoral positions. We are specifically looking for candidates who possess a strong background in theoretical and computational modeling