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that connect animal health, data analysis, and human behavior. Design and carry out field studies, collecting and analyzing large data sets. Use and evaluate AI tools to support research and training. Create
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research focused on advancing Precision Menopausal Hormone Therapy (P-MHT) for women worldwide. Integrate and analyze large-scale human datasets, including electronic health records, claims data, and omics
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available within the Department of Medicine, Division of Endocrinology in the Laboratory of Brain Behavior and Big Data at the University of Southern California. The applicant with work with PI and
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Stroke Research and Prevention Group of HKU (stroke.hku.hk) to assist in neuroimaging data acquisition and analysis, write-up of the results, as well as training of students Apply image analysis skills
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emerging autonomous vehicles. The whole project encompasses a broad spectrum of academic, industrial and societal partners and includes a large group or researchers. The postdoc position will advance state
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motivated Neuroscience postdoctoral fellow. In addition to neuroscience research experience, having familiar with machine learning/AI/ big data processing will be an asset. A major part of this PDF
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desirable. Strong analytical capabilities and proficiency in the quantitative analysis of large datasets are also required. Click the 'Apply' button below to register an account with our recruitment system
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rules which enable effective learning in large and deep networks and is consistent with biological data on learning in the cortex. In particular, the research will focus on evaluating and extending a
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. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics for real-time battery health monitoring and fault detection. Collaborate with
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satisfactory performance and funding availability. Applicants should possess a Ph.D. degree in epidemiology, biostatistics, applied mathematics, data science or other related disciplines. They should have strong