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Overview We are seeking a highly motivated postdoctoral researcher with expertise in artificial intelligence and machine learning (AI/ML) to join our interdisciplinary team at Duke University. The postdoc
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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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, United States of America [map ] Subject Areas: Computer Science Machine Learning Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Appl Deadline: none (posted 2025/08
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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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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and
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conduct policies about other schools at Duke University. Compliance with all applicable University and departmental policies and procedures. The postdoc candidate is expected to: 1)Development of machine
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control
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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
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that the requisite degree be conferred before a petition can be filed or a visa document tissued to sponsor the individual. The term of the appointment is limited (see Section 5 of the Postdoc Policy for length
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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