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include applications of neural networks to the analysis of multi-omic data, models for predicting phenotypes using genotype data, biological data integration, etc. Participation in these projects will
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for machine learning in materials science, you will work in close collaboration with members of the WASP-WISE pilot project on predicting moisture content in timber drying using machine learning
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deep learning models (e.g., adapting methods in [6]) based on spatial cellular graphs constructed from these images to predict clinical outcomes. The research will be carried out using two
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risk indicator for predicting myopia onset in children. Ophthalmic Physiol Opt. 2024; 00: 1–17. https://doi.org/10.1111/opo.13401 Naidoo KS, et al. Potential Lost Productivity Resulting from the Global
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pathogenesis and their potential as therapeutic agents and diagnostic tools. Using in vitro, ex vivo, and in vivo models, the lab studies EVs derived from amniotic fluid stem cells (AFSCs) and other perinatal
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the creation of accessibility letters for student-athletes with disabilities. Work with the office of Enrollment Management to use a data model that aids in the prediction of student success and encourages a
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analytics, predictive modeling, and related fields. We welcome applicants committed to addressing complex challenges in sport analytics, tourism analytics, human performance, and related fields. Candidates
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relying on up-to-date research, the program strives to help growers produce high quality vegetables while minimizing pesticide inputs. The program also develops real-time GIS-based predictive models of pest
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, case-control studies, cohort studies, structural equation modeling, geospatial modeling, missing data, population-level risk prediction, and measurement errors Community-based research, health
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biotechnology tools • Cognitive neuroscience • Psychological and brain sciences • Medical • Biomedical • Nanofluidics and microfluidics • Biomimetics and biofilms • Social media analysis and predictive modeling