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Tomalak XI. Nuclear Theory Group Recruit Information Our group invites applications to fill up 1-2 postdoctoral positions for the study of nuclear fusion, nuclear fission, and structure and synthesis
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include: Developing deep learning models for spatiotemporal fusion of multi-sensor satellite data (e.g. SAR and SMAP), with soil moisture as a target variable. Designing and evaluating deep learning
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USDOT-funded, multi-year R-SEAT (Rural Safe Efficient Advanced Transportation) Center research, collaborating with consortium universities and local DOT partners on pilot projects, data fusion efforts
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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, atmospheric signals), data fusion across sensing modalities, and development of scalable machine learning pipelines. Work will be entirely computational and based in Seattle, with no field deployment
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. However, very little work has been performed on system/network optimization while considering the communications requirements jointly with the decision fusion process. This approach will produce novel
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, and antimicrobial resistance. Helps in developing fundable proposals, leading to research projects that advance current scientific knowledge. Assist other lab members accomplish their research tasks
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series of publishable contributions to knowledge which answer important questions in the field of molecular biology of paramyxoviruses, pneumoviruses, and coronaviruses; represent an important contribution
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time of employment, and the degree may be in sociology, psychology, political science, or related areas. Demonstrated knowledge of statistics and research experience of social surveys of an East Asian
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to strengthening the position of New Approach Methodologies (NAMs) within the national and international regulatory ecosystem. Your focus will be on unlocking and applying regulatory knowledge to accelerate