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, United States of America [map ] Subject Areas: Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Computer Science Machine Learning Appl Deadline: none (posted 2025/08
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regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. The Postdoctoral Associate will conduct research in statistical machine learning and
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competitive benefits program, which includes medical, dental, and vision insurance, retirement contributions, employee discounts, vacation and sick time, and more. Please review the Summary of Postdoctoral
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) Experimental investigation and computational model simulation of laser-induced bubble dynamics and material damage assessment 3) Developing AI and machine learning models for robot-assisted laser surgery and
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oral history work, with regard to Beyond the Veil and the SNCC Legacy Project, the multifaceted history of Duke, and a range of other initiatives. The History Department has a vibrant Ph.D. program, and
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neuroscience broadly defined (e.g., Psychology, Neuroscience, Computer Science, or a related field) are welcome to apply. Experience with computational modeling is required. Strengths in open science practices
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activities ● Present results at collaboration meetings and scientific conferences Required Qualifications: ● Ph.D. in Physics, Astronomy, Astrophysics, Computer Science or a related field by the start date
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PhD with an interest in computational social science or data science (broadly defined). This individual will help design, execute, and analyze a series of field experiments on a platform created by the
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Experience- Preferred--device design, fabrication and testing with microfabrication and integrated photonic devices. Skills- Preferred--Quantum software, quantum computing Duke is an Equal Opportunity Employer
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: Leveraging big data and computational methods to analyze adaptation behaviors and incorporate its costs and benefits into climate impact assessments. • Adaptation of Places: Partnering with natural scientists