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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 10 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique
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Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable autonomous and efficient network/service management. The PhD candidate will investigate innovative
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and numerical models as well as constitutive model calibration and validation based on physical experimental data. Required Qualifications: A successful applicant must have a PhD in Engineering
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million. For further information about our School, please visit - https://www.unsw.edu.au/engineering/our-schools/electrical-engineering-telecommunications Skills & Experience A PhD (or soon to be awarded
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machine learning for biomedical applications. Preferred Qualifications Programming in C++. Required Documents Resume To be considered for this position please visit our web site and apply on line at the
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to knowledge in one or more of the following areas: machine learning, cybersecurity, or computer systems Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in
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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
abiotic resources. We integrate remotely sensed information with in-situ data, process-based models, and leverage satellite communication, IoT and machine learning technologies in order to provide evidence
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Technology (IST) has 44 full-time faculty members with research foci in cybersecurity, data mining and machine learning, natural language processing, human-centered computing, and computing and engineering
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through applied research programmes. Faculty in the ICT Cluster undertake funded industry-relevant research, teach courses in Computer Science, Computer Engineering, Information Security and Software