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(SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience
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. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological modelling, with an emphasis
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learning, and data science, with a particular focus on neuroscience applications. Designs AI techniques and algorithms for multimodal data fusion (e.g., MRI, EEG, cognitive and behavioral data, blood
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industry partners. Design, implement, and validate advanced reinforcement learning models. Utilize reinforcement learning and evolutionary algorithms to discover new chemical materials. Publish and present
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algorithms, clinical decision support systems, and population health management platforms. Evaluate emerging technologies in clinical informatics and provide strategic recommendations for their adoption within
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formats. Experience with AI and deep learning algorithm development for medical image analysis. Familiarity with SQL, Python, Tensorflow, Scikit-Learn, and Pandas. Additional Qualifications Considered
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team to develop integrated control algorithms for autonomous cubesatellite formation flying. The controllers that will be developed during this project will differ from previous work on this topic by
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algorithmic advances and aim at publishing them at these top venues. More details about the position can be found here. As a KAUST postdoc or researcher, you will have access to state-of-the-art research
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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learning or deep learning research project; (b) evaluate the proposed algorithms; and (c) conduct a real-case analysis. Qualifications For the Research Fellow post, applicants should have a doctoral