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using both physical and machine learning-based algorithms. Strong interpersonal and communication skills and the ability to work both independently and collaboratively with researchers and students from
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implementing algorithms based on online Sparse Gaussian Processes and advanced probabilistic techniques enabling AUVs to dynamically alter their trajectories, cutting down on uncertainty and improving efficiency
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-powered diagnostic algorithms, and integration with digital health platforms for real-time monitoring and clinical decision support. WITEC brings together interdisciplinary researchers from MIT and
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to ensure that the developed notations and algorithms address the companies’ needs. More about the related project can be found here: https://innovationsfonden.dk/da/news-article/ai-skal-forudsige-og-forklare
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these autonomy and self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
include (but are not limited to): Develop algorithms to characterize aerosol speciation from LIDAR fluorescence signals Develop machine learning emulators to represent forward operators for polarimeter-only
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We offer PostDoc positions in the area of Quantum Software Verification, Compilation and Optimization. Interested applicants with strong analytical skills and a desire to work on algorithmic and
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. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing multidimensional networks by studying the theoretical foundations behind randomized
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highly complex workflows. We aim to develop optimization models and algorithms to improve wafer processing sequences across semiconductor manufacturing tools, with the objectives of reducing cycle times
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methodology will involve the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation