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settings and (ii) explicit task execution knowledge embedded in multi-modal documents. This research will specifically look at the development of embodied and embedded intelligence, which allows AI-based
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. Qualifications Required Qualifications: Completed PhD in biomedical engineering, electrical engineering, physics, or a medical imaging related field. Experience with developing advanced pulse sequences
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Responsibilities The PDA will conduct research to design and develop optical wireless communication systems. This involves the development of mathematical models for signal transmission/reception, derivation
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of the algorithms developed in this project. About you The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance
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structure-preserving discretization algorithms (a refinement of finite-element analysis compatible with exact geometric, topological, and physical constraints) with artificial neural networks for achieving
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, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be on creating and optimizing state
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 3 months ago
questions in Earth System science is also a goal of this opportunity. Efforts are expected to be conducted in collaboration with the SAGE algorithm/data processing and validation teams, as
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 months ago
of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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party within 90 days before the expiry date of the initial contract or of the renewal, based on an unfavourable evaluation of the work developed by the post-doctoral researcher, carried out under
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and