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demonstrable equivalent professional experience. They will also have strong experience of using machine learning or data science to analyse and model large datasets. Demonstrable technical knowledge and skills
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leadership and governance. About You We are looking for a strategic, collaborative, and inclusive leader who brings: Essential: Significant experience in a senior digital or IT leadership role within a large
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. Validate and analyze system space data. Collaborate with institutional leadership for capital program, divisional and system-wide framework planning. Lead programming and planning process for large projects
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. Machine/Deep learning techniques -- 3.2. Data management/curation, analysis, processing and exploitation -- 3.3. Generative AI and Large Language Models (LLM) such as GPT and open-source equivalents --3.4
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University of California, Los Angeles | Los Angeles, California | United States | about 19 hours ago
in addition to complex Digital Librarian computer job duties. The Admin Assistant III demonstrates complex and advanced EMIR Quality Assurance and PACS Image Quality Assurance competencies, following
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(VMTH) includes the Small Animal Hospital http://vethospital.tamu.edu/small http://vethospital.tamu.edu/small-animal-hospital animal - hospital and the Large Animal Hospital http://vethospital.tamu.edu
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: A Ph.D. in biomedical informatics, computer science, information science, data science, (bio)-statistics, (applied
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the research project - “COMAC-PolyU Research institute for large aircraft (RILA)”. Qualifications Applicants should have an honours degree with knowledge of Aerospace and Aviation Engineering. Preference will be
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the Computational Rare Disease Genomics (CRDG) Team, which is led by Associate Professor Nicky Whiffin and based within the University of Oxford’s Big Data Institute. The CRDG team collectively use
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, such as single-cell omics, cellular electron microscopy, and optical microscopy data sets. Additional work may entail integrating large-scale cross-sectional data with more limited time-course information