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Field
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data
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generation algorithm based on different approaches to improve understanding the behavior of forecasting algorithms in time series and tabular data. The workplan will be as follows: Literature review Design of
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algorithms for mobile robots. Implement and accelerate visual algorithms for mobile robots on embedded platforms. Develop a visual embedded platform on a mobile robot. Conduct field trials with the robotic
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polarization states. • Data Analysis & ML: Develop Python/MATLAB machine learning algorithms to map photocurrents to full Stokes parameters, targeting a reconstruction error of \(<1\%\). Required
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data analytics; Development of marine geophysical survey and machine learning algorithms; Process geophysical/geomechanical data and analyze the data using machine learning; Conduct research, supervise
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regulation”. The appointees will be required to: (a) develop multi-agent systems; (b) assist in recommendation, payment and regulation algorithm design; (c) provide support in experimental result
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Job Description We are looking for a Research Fellow under the National University of Singapore (NUS) to support a project investigating the fundamental theoretical and algorithmic performance
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applications including asset pricing, volatility modelling, risk management etc. Developing the framework of economic world models, with generative AI algorithms such as diffusion models and theory-informed
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of algorithms for medical image analysis. The successful candidate will investigate computational complexity, stability, and numerical summaries of multiparameter persistence, as well as applications to medical
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that important physical properties are fulfilled in the numerical solution. Ultimately, PANum will lead to a computational algorithm that reliably simulates two-phase flow. The postdoctoral project will be part of