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Field
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. Biomedical Informatics is an interdisciplinary field at the intersection of biology, medicine, and quantitative sciences. Biomedical Informatics researchers develop new methods to integrate and analyze vast
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, sometimes from multiple jurisdictions, to achieve sample sizes appropriate for training algorithms. This creates challenges with data security and data flows (due to legislative restrictions). Further, data
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capabilities to support nuclear security missions. The research involves development and testing of novel data analytics processes and specialized algorithms to improve measurement efficiency and reduce
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and algorithms. Train, test, and optimize AI/ML models for production environments. Integrate AI/ML components into web-based and backend systems. Ensure security, scalability, and maintainability
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Cornell faculty members and the project’s co-principal investigators (from multiple organizations) to oversee a cross-organizational research team consisting of a group of postdoctoral associates, PhD
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novel algorithms for pattern detection, extreme event attribution, and seasonal forecasting. Lead development of innovative visualization techniques and interpretable machine learning methods (30%). Drive
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science, including supervising team members, developing novel algorithms for pattern detection, extreme event attribution, and seasonal forecasting. Lead development of innovative visualization techniques
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Staff - Non Union Job Category M&P - AAPS Job Profile AAPS Salaried - Scientific Eng., Level A Job Title Software Engineer, IoT Department UBCO | Research Support | Bourbonnais | Department of Earth
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the process to maintain standards, technical infrastructure, data management and data algorithm development efforts for future uses, as well as a compliance review. Implements recommended data deficiencies
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algorithms. Train, test, and optimize AI/ML models for production environments. Integrate AI/ML components into web-based and backend systems. Ensure security, scalability, and maintainability of applications