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impact-based health early warning systems. The successful candidate will join the research team of Dr. Joan Ballester Claramunt (https://www.joanballester.eu/ ) at ISGlobal within the framework
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network performance data obtained from user devices. Assist in the development of basic models to predict or explain network behaviour under different conditions. Contribute to the improvement of internal
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fundamental and applied challenges in how unsteady flows generate sound and how that sound can be predicted or reduced. For more information please visit - https://www.unsw.edu.au/research/flownoise Skills
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Optimization (AI/ML) Developing AI/ML models to predict drillability issues based on mechanical rock properties Real-time parameter optimization (WOB, RPM, flow rate, etc.) using machine learning techniques
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of Molecular Medicine and Therapeutics at The Ohio State University College of Medicine. Lab website: http://u.osu.edu/mathur Our goal is to use the lens of metabolism to better understand and predict cancer
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in fault detection, diagnostics (FDD), and preventative/predictive maintenance for industrial systems. The role is part of the EU-funded FLARE project, which focuses on improving industrial resilience
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neuroscience • Psychological and brain sciences • Medical • Biomedical • Nanofluidics and microfluidics • Biomimetics and biofilms • Social media analysis and predictive modeling • Molecular, cellular
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nursing science, applied to nursing practice and care processes, including digital care pathways, predictive and preventive models, and data-informed clinical decision-making. The professorship emphasises
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
to develop machine learning-enabled approaches for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building
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derived spheroids Develop predictive model of drug response by comparing 2D to 3D cellular systems Testing and validating the relevance of such models in patient tumour specimens Support and preparation