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at prediction and pattern recognition tasks but still fails at very simple planning and decision-making problems. This project will develop predictive and prescriptive analytics algorithms that combine
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simulation of scenarios with different materials and geometries. - Support the development and implementation of signal and image processing algorithms, including fast inversion techniques, FFT, and nonlinear
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strong foundation in programming (e.g. Python) and core concepts in machine learning or data analysis. Ability to engage with research literature and develop analytical, problem-solving, and algorithmic
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Processes and developing AI algorithms for image processing and analysis. Years of Research ExperienceNone Internal Application form(s) needed Normalitzat_Cvi_registreiseguiment_english_4.pdf English (47.04
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Tenure-track Assistant and Associate Professorship positions in Data Science and Machine Learning...
, the position can be at our established campus in Odense or at our developing new campus in Vejle. What we are looking for We are looking for new colleagues who can strengthen or add to our competences in
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Computational Circular Design: Development, scalability and computational efficiency of surrogate-assisted many-objective optimisation algorithms for circular design for disassembly (C3.5-AMR
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oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. In research and academic
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develop cutting-edge algorithms and AI-based solutions for data processing and validation and provide scientific expertise for the implementation of future remote sensing missions. The team’s work bridges
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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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On-device machine learning (ML) is rapidly gaining popularity on mobile devices. Mobile developers can use on-device ML to enable ML features at users’ mobile devices, such as face recognition