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: Bayesian Machine Learning – Led by Dr Thang Bui, this project focuses on sequential decision-making and bridging deep learning theory and practice. Applicants with expertise in probabilistic modelling
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computing, and database development and management. Background in computational modeling and machine learning. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully
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groups led primarily by Professor Tarek Abdoun and Professor Mostafa Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development
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, integrity, and optimal integration across diverse data sources. Conduct comprehensive data analyses, including standard statistical methods, advanced predictive modeling, machine learning techniques, and
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evaluations in controlled environments. Essential Function Yes Percentage of Time 10 Job Duty Continuous Learning and Innovation Stay up-to-date on emerging AI models, frameworks, and best practices
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Demonstrated research experience in computational physics, machine learning, or related areas. Practical experience in developing novel AI/ML models and algorithms. Experience collaborating in multidisciplinary
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goals and contribute to resilient, future-ready energy systems Key Responsibilities: 1) Develop Forecasting Models Design and implement statistical and machine learning models to predict energy demand
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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We are seeking a part-time Research Programmer/Analyst in computer vision and machine learning for human behavior analysis and modeling to connect different science disciplines. The successful
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datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep learning architectures including generative models, particularly