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position. The lab studies cognitive control using behavioral/modeling, fMRI, EEG, and TMS approaches. The Postdoctoral Associate will build specifically on our ongoing research examining neurocognitive
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. quantitative and/or qualitative counterfactual-based approaches, Difference in Difference models, Qualitative Comparative Analysis, Bayesian hierarchical modelling); o Experience working with and synthesizing
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requires working with large data sets related to parenting and child development across multiple sites in the United States, helping to prepare data and estimate models for a variety of research papers, and
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science. Other application areas of interest include robust parameter estimation and performance bounds under model misspecification, integrated sensing and communications, orthogonal time frequency space
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Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and
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biology, and mechanisms of drug resistance. Research activities will utilize a combination of in vitro approaches, including cultured cell models, and in vivo experimental systems using animal models
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academic institutions. Individual will develop and test novel computational models of the neural activity generated by electrical stimulation of the brain. Also, perform data analysis utilizing medical
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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