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                models that include these mechanisms. The postdoc will develop biologically-constrained machine learning–based model discovery pipelines to derive interpretable surrogate ODE/PDE models from simulated ABM 
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                the individual. The term of the appointment is limited (see Section 5 of the Postdoc Policy for length of appointment). The appointment involves substantially full-time research or scholarship, and may include 
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                starting the postdoc and must have prior publications. To apply, please submit a cover letter, CV, statement of research interest, names and contact information for three references and a publication list 
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                conferred before a petition can be filed or a visa document issued to sponsor the individual. The term of the appointment is limited (see Section 5 of the Postdoc Policy for length of appointment 
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                simulations to identify key mechanistic drivers of viral persistence and immune response, and use SciML to automatically select ODE/PDE models that include these mechanisms. The postdoc will develop 
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                . The Department of Cell Biology is looking for a postdoc candidate to conduct research on tissue morphogenesis using zebrafish as a model system. The candidate will ideally have a training in 
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                is limited (see Section 5 of the Postdoc Policy for the length of the appointment). The appointment involves substantially full-time research or scholarship and may include teaching responsibilities 
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                Duke University, NSOE-ESS & MSC Position ID: Duke-NSOE-ESS & MSC-POSTDOC [#30156] Position Title: Position Location: Beaufort, North Carolina 28576, United States of America [map ] Subject Areas 
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                sponsor the individual. The term of the appointment is limited (see Section 5 of the Postdoc Policy for length of appointment). The appointment involves substantially full-time research or scholarship, and 
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                policies pertaining to other schools at Duke University. The postdoc candidate is expected to: 1) Develop novel methods for incorporating scientific machine learning in solving problems in solid mechanics