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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
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robust models – and for clinicians, whose goal is to determine when to trust the models. We therefore seek candidates who have strong technical background in working with large-scale deep learning models
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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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analyzing publicly available data on employment, education and higher education residing in large federal data sets (e.g., Census data, NCES data). Conducts research and prepares project-related technical
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management tools. This role involves designing and executing large-scale epidemiological studies using EHR data, overseeing clinical data annotation/processing from public and Hospital Authority sources, and
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Zhejiang Province), and Data Science and Big Data Technology. Additionally, there is a dual bachelor's degree program in "Information and Computing Science + Automation." Teaching Resources: The school
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(e.g., Reinforcement Learning, Agent Based Modelling) to join our team full-time as part of a large international collaboration of European researchers (incl. Tobias Dienlin, Veronica Kalmus, Adrian
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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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, molecular biology, immunology, pharmacology. Attention to detail, ability to record and manage large data files, and ability to coordinate assignments on a day-to-day basis. Contact information for three
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required Working knowledge of all aspects of planning and deploying an AI project, including initial problem specification, data gathering and analysis, model creation, and implementation Strong