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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io
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2022 but may also start earlier. KAUST offers competitive/generous postdoc compensations. The Research Vision-CAIR group performs research and develops computational approaches in the following research
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transmission of information and energy, systems theory, and computational hardware and software. ECE students are encouraged to develop synergies with disciplines outside of engineering. The candidate should
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of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between
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candidates will have specialist knowledge in signal processing and algorithm design, with experience in machine learning, AI system development and reinforcement learning along with a strong publication record
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
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imaging (MRI). The Computational Biomedical Imaging Group (CBIG) pursues research on the development of new algorithms for the reconstruction and post-processing of medical and biological images. Active
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and prioritize impactful software solutions and guide the team in developing creative, robust approaches to evolving research challenges. Apply AI/ML algorithms to domain-specific software engineering
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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turbine blades. Successful re-development for end-of-life composites could enable reuse in other structural applications. This PhD will investigate the development of hierarchical Bayesian algorithms