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surveillance, random testing, wastewater, hospital surveillance) may help optimize epidemic monitoring, iii) modelling and comparing the patterns of spread of COVID-19, influenza and RSV by age group in France
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monitoring. Design and implement machine learning models to analyze multimodal data (e.g., student behavior, engagement, and performance) to enhance personalized learning. Develop and evaluate GPT-powered AI
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to numerous preclinical research projects focused on the development of novel molecular magnetic resonance imaging (MRI)-based techniques for early detection, disease phenotyping and monitoring treatment
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validation to improve understanding and prediction of subsurface processes. Outstanding UA benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU
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presence in the broader context of the drastic effects of climate-induced changes and address questions related to improving management, such as: How can vulnerable areas best be monitored? Can local noise
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Conservation D. How plant cell shape and tissue structure help cells stick together E. DETERMINER - Determining appropriate monitoring frequency for phytoplankton F. Predicting bacterial protein expression
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Job Title Postdoctoral Research Associate Agency Texas A&M University Health Science Center Department Medical Physiology Proposed Minimum Salary Commensurate Job Location Bryan, Texas Job Type
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
, and Precision Health. The project aims to leverage AI and machine learning (ML) to analyze complex metabolomics datasets and address key health challenges, including biomarker discovery, disease
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Med Overview New Jersey’s academic health center, Rutgers Biomedical and Health Sciences (RBHS) takes an integrated approach to educating students, providing clinical care, and conducting research, all
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AgriLife and make a difference in the world! This position provides leadership to the analysis, synthesis, and publication of (a) continuous monitoring data and (b) residual data sets from research campaigns