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, United States of America [map ] Appl Deadline: (posted 2025/09/04, listed until 2026/02/20) Position Description: Apply Position Description Postdoctoral Associate – Scientific Machine Learning for Multiscale Biological
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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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and mathematical modeling, hierarchical statistical modeling, machine learning, remote sensing, geospatial statistics) • Demonstrated ability to conduct independent research and publish high-quality
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University invites applicants for a Postdoctoral Associate to work with faculty. The postdoctoral fellow will (1) teach one section of Incarceration Nation per academic year, with the possibility of teaching
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analysis using appropriate machine learning techniques and contribute to the writing of technical papers and research proposals. Duke is an Equal Opportunity Employer committed to providing employment
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, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at https://hr.duke.edu/benefits/ Duke is an Equal Opportunity Employer committed
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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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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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the ability to work together with colleagues and teach and mentor students from diverse backgrounds and perspectives. To apply, candidates should submit a cover letter, curriculum vitae, and contact information
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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