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other Duke faculty, or faculty at other academic institutions. Individual will develop and test novel computational models of the neural activity generated by electrical stimulation of the brain. Also
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digital health and multi-agentic coordination. This role requires the development of self-learning artificial intelligence models tailored for dynamic healthcare environments. The candidate designs and
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holography and electronic systems for control and analysis of instruments, applying these systems to the study of human diseases, and acquiring and analyzing clinical data sets. Programming skills should
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advanced epidemiologic and biostatistical methods, including causal inference, survival and longitudinal modeling, and approaches for integrating multi-level and high-dimensional data. There will be
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into interactive or XR systems (e.g., perception, tracking, adaptive systems, user modeling) (Preferred) Experience collaborating with healthcare professionals or working on healthcare-related technologies EDUCATION
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model for other faculty, postdoctoral associates, graduate clinicians, and staff. Preferred Qualifications: Clinical experience and appropriate training in delivering behavioral pain and symptom
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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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of Medicine—are seeking a post‑doctoral scientist to contribute quantitative and modeling expertise to two major research projects. The principal investigator of the first project, Professor Osondu Ogbuoji, is
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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell
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postdoc associate. The individual will implement, simulate and analyze models of epileptic source localization from EEG signals. Collaborate with clinicians to obtain and analyze imaging, EEG, and outcome