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Foundation RECRUIT grant ("Data Management, Algorithms, & Machine Learning for Emerging Problems in Large Networks – with Interdisciplinary Applications in Life & Health Sciences". NNF22OC0072415
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obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. This postdoc position will utilize
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the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. The postdoc will be part of the Microbial Metagenomics group
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. The work includes theoretical analysis, algorithm design, and validation on realistic case studies, as well as dissemination of results through publications, open-source code, and collaboration with internal
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validation (V&V) techniques for space systems, software and algorithms with a focus on specific challenges of space-borne perception and proximity operations uncooperative spacecraft . Develop novel methods
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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
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particular focus on applications relevant to the Arab world. The successful applicant will join a multidisciplinary research team working at the intersection of machine learning, algorithmic fairness, human
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research for understanding the learned algorithms in brains and machines. The post holder will provide guidance to less experienced members of the research group, including postdocs, research assistants
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algorithms where the agent can propose updates to its own world model structure, but these updates are only accepted after a formal verification step confirms that the new model still adheres to its core
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data for urban characterization. The work includes developing algorithms, performing large-scale analyses, and collaborating with partners across disciplines in remote sensing, urban studies, and climate