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the development of seaborne trade, shipping and maritime networks from the sixteenth to the nineteenth centuries. It will bring together large quantities of previously fragmented archival evidence from across
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the precision health domain that aim at diagnosing various types of disease and recommending optimal treatments for patients. The position will be supervised by Research Professors and will be conducted with
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, under the primary supervision of Dr. Murthy, with close collaboration with Dr. Goonewardena and a broad network of national and international research partners. The fellow will lead multi-omic analyses
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related to this job in PI (Nanyang Assistant Professor Guangwei Hu): https://dr.ntu.edu.sg/cris/rp/rp02126 . We are looking for a Postdoctoral Fellow to support research works in COEB. The role will focus
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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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of parametric studies, analysis and optimization of solutions based on acoustic metamaterials; - participation in the evaluation of the application of the developed concept, namely through the simulation of real
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economic benefit and positive change in the world. You will have proven ability to provide research leadership, build teams, develop networks, and manage collaborative partnered research projects in a global
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grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Dr Yingzhen Li (https://yingzhenli.net ) and her research group
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on research projects spanning evaluation of deep learning neural networks trained on signed language recognition. The fellow will work closely with the PI Annemarie Kocab and collaborator Alex Lu , Senior
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on hardware and software co-design for systems targeting energy-efficient chips. The role involves developing, evaluating, and optimizing system-level techniques across hardware architecture, software stack