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Field
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and algorithms for digital twin verification, validation and uncertainty quantification. Develop, demonstrate, and apply methods in a range of complex system application areas, including aerospace
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), to work on problems at the intersection of biology, medicine, mathematics and computation. The successful candidate will contribute to the development of next-generation learning algorithms to understand
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computer vision algorithms and implementing these for specific clinical projects. 80% algorithm development, 20% deliverables (written and oral), all under the direction of the PI. Department Description
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-cell and spatial-omics research. The ideal fellow will be interested in developing and applying novel computational algorithms to novel datasets generated in the setting of non-neoplastic and neoplastic
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, operating systems, programming languages, formal methods, real-time systems, security and cryptography, and theory of computation and algorithms. In addition, members of the Department collaborate closely
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Design and apply deep reinforcement learning algorithms for online HVAC control in greenhouses and for data mapping with multi-robot systems. Implement and test algorithms in simulation and
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of Device Bioengineering, including but not limited to the development and implementation of approaches that interface with living systems through novel materials and algorithms, electric and magnetic fields
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figures of lab members. Candidate will train on the lab’s fundamental algorithms and run them in a collaborative manner with other team members to generate paper figures and make discoveries. Collaborative
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research associate position in AI for science. The Learning Systems Group seeks a postdoctoral researcher specializing in federated learning and privacy-preservation algorithms. The successful candidate will
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The Institute for Data, Econometrics, Algorithms, and Learning (IDEAL). Northwestern, TTIC, and UIC. Position ID: Northwestern-The Institute for Data, Econometrics, Algorithms, and Learning (IDEAL