64 parallel-computing-numerical-methods positions at Indiana University in Postdoctoral in United States
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questions, advancing deep learning models, or other topics discussed with the PI. We use publicly available and simulated genomic data. Core job duties include: (1) Building computational pipelines
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biomedical imaging methods, with particular emphasis on optical, ultrasound, and photoacoustic technologies. Working under the supervision of Dr. Ying Jiang, the candidate will contribute to the development
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biomedical imaging methods, with particular emphasis on optical, ultrasound, and photoacoustic technologies. Working under the supervision of Dr. Ying Jiang, the candidate will contribute to the development
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trial access. This fellowship is designed to support the development of an early-career nurse scientist pursuing an independent program of research focused on health equity, health disparities, ethics
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methods, work with real messy multi-source data, and contribute to infrastructure supporting population-level research and health equity. The postdoctoral fellow will be based in the Department
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applications for a Postdoctoral Fellow to join the Human Evolutionary and Statistical Genetics (HESG) Lab. The HESG Lab develops statistical and computational methods to understand human population history and
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-time, and evidence-accumulation phenomena. Implement simulation, parameter-estimation, and model-comparison methods in Python, MATLAB, R, or related computational environments. Lead and co-author
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for spatial population genetics. Our research integrates custom neural architecture design, simulations, and publicly available genomic datasets to develop new inference methods. The Postdoctoral Associate will
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. The chemical biology area of the Department of Chemistry is located in Simon Hall, home to our graduate training program in Quantitative and Chemical Biology and nearby other biochemists and structural
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translate these discoveries into precision medicine. We develop computational and statistical methods while integrating human genetics, single-cell and multi-omics, large-scale biobank resources, and