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practices ● Fluency in programming languages such as R and Python. ● Demonstrated ability to make reproducible code for cleaning, integrating, and modeling spatial/temporal data from multiple sources, spatial
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to independently design and generate simulations using the Regional Oceanic Modeling System (ROMS) or other related codes (e.g., COAWST, CROCO, MITgcm, Oceananigans) in realistic and/or idealized configurations
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decision-making, with a focus on dopamine neural coding and its dysfunction. Please see: Amo et al., Neuron, 2024 (https://www.cell.com/neuron/fulltext/S0896-6273(23)00979-0 ) Amo et al., Nature Neuroscience
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Previous Job Job Title Post-Doctoral Associate Next Job Apply for Job Job ID 368970 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job Code 9546 Employee
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Department Name SURGERY Location Code SURGERY (06740A) Is this split and/or fully grant funded? Yes Duties and Responsibilities The Post-Doctoral Fellow will have a joint appointment with the Department
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Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job About the Job: We are seeking a motivated and productive post doctoral associate with experience
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findings in peer-reviewed journals and present at conferences. Other Requirements and Factors REQUIRED This position is security sensitive. This position requires compliance with state and federal laws/codes
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, reports, and proposals Document procedures; curate and preserve data Some coding/ scripting Perform other related duties as assigned Adaptability, excellence, and passion are vital qualities within Carnegie
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of the research group and others as described in the Duke University School of Medicine Honor Code of Professional Conduct and other relevant conduct policies pertaining to other schools at Duke University
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, neural engineering, and data analytics. Among the key duties of this position are the following: Collecting behavioral and electrophysiological data in the clinical environment. Writing replicable code