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-award courses of Higher Education Institutions. Preference factors: Machine Learning Knowledge. Knowledge of signal processing and machine learning libraries (e.g., PyCaret, scikit-learn). Minimum
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to treatment, population health monitoring, workforce development and leadership, policy, and advocacy. Background The Robotics, Autonomy and Machine Intelligence (RAMI) Group led by Prof Nabil Aouf is dedicated
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for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service
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qualification/experience in a related field of study. The successful applicant will have expertise in statistical modelling, epidemiology or machine learning and possess sufficient specialist knowledge in
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, including physical, cognitive, and psychosocial status. Orders and interprets laboratory and diagnostic tests. Develops pharmaceutical and non-pharmaceutical treatment plans. Monitors effectiveness of plan
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engineering, including machine learning, sustainable construction, climate adaptation, and intelligent tools. Demonstrate future contributions to capacity-building and socio-economic advancement after
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proven interest in AI foundations and its application in civil and environmental engineering, including machine learning, sustainable construction, climate adaptation, and intelligent tools. Demonstrate
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biological science and civilian mapping agency, USGS collects, monitors, analyzes, and provides science about natural resource conditions, issues, and problems. Research Project: Science synthesis and
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analyses of these data for research, quality improvement and surveillance purposes. The incumbent will apply appropriate methods to aid in the creation of a learning health system around opioid-related
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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods