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looking for postdoctoral researchers in the area of computer vision, AI, and machine learning. The initial appointment will be for 2 years with a possible extension with a tentative start date in January
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The VCC center at KAUST is looking for postdoctoral researchers and research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep
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single-cell and single-nucleus multi-omics, machine learning/AI, computational biology, and experimental validation to understand cardiovascular disease progression and identify novel therapeutic targets
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designing and building visualization dashboards. Research experience in human-centered AI, or in the integration of AI and machine learning methods into interactive visualization and analysis systems. Strong
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Qualifications PhD. required. Additional Qualifications Experience/interest in programming language, verification, artificial intelligence or machine learning. Individuals with a demonstrated track record in
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the postdoctoral program where together with you we will prepare a career plan, which contains the skills and knowledge you will acquire Open and inclusive working environment with committed colleagues Favorable
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novel findings that inform disease etiology. The candidate should be interested in focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research
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Details Title Postdoctoral Fellowship in Electrical and Computer Engineering School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science Position
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Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 2 months ago
genetic data Multimodal machine learning for biological discovery Translational genomics and risk modeling The fellow will work in an environment that emphasizes methodological innovation, statistical rigor
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opportunities within the company. Responsibilities Develop and implement advanced computational and machine learning strategies, including deep learning, graph-based methods, and probabilistic modeling