793 algorithm-"Multiple"-"U"-"Prof"-"Simons-Foundation"-"University-of-Wisconsin-Madison" positions in Australia
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to research-based activities, including the development of new data analysis algorithms, processing and analysis of field data, and participation in the fieldwork. Your responsibilities will include: Conduct
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maintain a streamlined shared services framework; provide problem solving of requested support by academic staff and other stakeholders; support multiple facets of the academic and delivery lifecycle
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publicly available datasets; 3) Proposing algorithms aimed at improving the accuracy of human activity detection; 4) Implementing these algorithms, evaluating their performance empirically, and comparing
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About you The successful candidate will demonstrate event management expertise, coordinating resources, managing timelines and budgets across multiple locations while understanding protocols
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Agreements are essential. The ability to manage multiple stakeholders, negotiate and influence outcomes, create thorough documentation, and provide training and user support are also critical to excelling in
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techniques for near-field microwave systems, design and test antennas/antenna arrays for near-field microwave imaging, model and simulate antenna and algorithm performance, participate in lab testing, write
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to higher education. About the role You will assist in the delivery of integrated domestic and international marketing campaigns across multiple paid and owned digital and traditional channels to support
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This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain
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algorithm that allows accurate simulation of fluid transport processes in porous media coupled with chemical reactions (e.g. dissolution and precipitation). The algorithm will be validated firstly against
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the headspace website. Possible approaches to addressing this challenge might include: Developing algorithms to identify patterns and preferences based on service users’ previous content engagement