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the global health scenario and domestically for dissemination, and plenty of opportunities for career advancement. •Learn background/research methods of studies for which analysis is conducted with limited
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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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field. - Evidence of strong prior experience analyzing large datasets using advanced econometric and statistical methods (using R, Stata, and/or Python). - Strong interest and experience working
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are open to all methods and humanistic fields of inquiry. All projects must include a collaborative element that engages students, faculty, or the wider community. Completed projects will be presented
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, and who have strong grounding in the methods and practice of oral history. The holder of this postdoc will teach two courses a year, one an introduction to oral history method and practice, and one
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simulation methods, GPU-accelerated computations, several programming languages, and presenting results to wide technical and non-technical audiences. Additionally, the candidate will also develop theory and
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, interdisciplinary collaboration, and group dynamics. Preference will be given to applicants with expertise in field experiments, survey methods, or quantitative data analysis. The postdoc will contribute to a new
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intellectual environment with access to Genomics and Proteomics core facilities, and a High Performance Computer Cluster. Additional support and resources are also offered through the Office of Postdoctoral
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imaging data, computer models, and statistical tools. The individual will prepare manuscripts and contribute to the development of grant proposals. The McIntyreLab currently conducts research in the areas
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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