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Assistant Professor - Information Systems, Operations Management, Supply Chain Management, and Busin
, natural language processing , computer vision , predictive analytics , and optimization . Experience with generative AI, large language models, automated decision systems, or AI ethics and governance is
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, and process improvements.? Project and Portfolio Management? Establish and lead a transparent portfolio governance model that balances strategic impact, risk, and organizational capacity.? Define how
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to predict thermal runaway on the cell level. The combustion and gas model developed on the cell level will then feed into the work to accurately predict thermal runaway on pack, module, and system levels
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, artificial intelligence and robotics, data science, cognitive and brain science and economics and finance. Leveraging its ‘4-in-1’ model of education and residential college system, UM provides all-round
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field. This approach is related to data assimilation, allowing for better prediction, control, and optimisation of turbulent systems in engineering, energy, and environmental applications
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. The Postdoctoral Associate will work under the direction of the Principal Investigator in building a first-of-its-kind Software as a Medical Device (SaMD) that predicts, detects, and manages SSIs by fusing RGB
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to work effectively in an interdisciplinary team. PREFERRED QUALIFICATIONS Experience with one or more of the following: knowledge graphs, graph machine learning, link prediction, representation learning
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].. [1] Salomonsen, C. "A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal [18F]FDG PET imaging. " EJNMMI Research, 2026. [2] Thomas, S
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, assess the health state of systems, and predict their future evolution and remaining useful life. The proposed approach integrates physics-based and data-driven modeling techniques, including machine
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learning (AI/ML) being a major focus. Many of the laboratory's interests center around the identification of small molecules using mass spectrometry data, and the use of language models to predict