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Field
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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
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data analysis and develop sophisticated mathematical models for simulating power system behaviors under various scenarios. Development and Testing: Design and develop control algorithms to enhance grid
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pioneering research and innovation hub in AI—one that will shape the way humans and machines collaborate for decades to come. Led by Prof. Usama Fayyad, the Institute for Experiential AI is built around the
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: Employing satellite observation and machine leaning to improve model representation of ice sheet surface melt”. The candidate will work under the direction of Prof Nowicki and in collaboration with multiple
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that amplify human potential. The successful candidate will engage in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems
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algorithms for advanced and multi-modality imaging. Work on system designs, physics models, computation, benchtop experiments with small animals, and clinical translation. Additional areas of interest are in
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and Ph.D. students. Research environment You will join the ‘Multiphysics Simulation and Optimisation’ (MSO) research group lead by Assc. Prof. Joe Alexandersen at SDU Mechanical Engineering (SDU-ME) in
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Regular Job Code 9742R5 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Required Qualifications: * Ph.D. or Masters with equivalent experience in Computational
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algorithms, and decision-support tool development. Responsibilities will include programming, analysing and interpreting data, and contributing to innovative solutions that support maritime decarbonisation
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Details Title Pre-Doctoral Fellowship (Prof Kreindler) School Faculty of Arts and Sciences Department/Area Position Description Professor Gabriel Kreindler is seeking a predoctoral fellow. The