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are seeking highly motivated Data Science/Machine Learning Research and Development Engineers to join our Computational Intelligence and Visualization Application Department of the Applied Research Laboratory
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Intelligence, or a closely related discipline. Strong research background in AI and machine learning, with a focus on efficient or accelerated models. Proven experience with model compression techniques, such as
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improving plant health using machine learning and artificial intelligence. Mentor(s): The mentor for this opportunity is Yulin Jia (yulin.jia@usda.gov ). If you have questions about the nature of the research
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About Flinders Our bold vision, captured in our Strategic Plan: Making a Difference: The 2025 Agenda, is to be internationally recognised as a world leader in research, an innovator in contemporary education, and the source of Australia’s most enterprising graduates. To realise this ambition, we...
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value scholarships. About the scholarship The Learning Potential Fund provides support through scholarships and bursaries to students in financial need. The Manoharan Learning Potential Fund Scholarship
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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Polytechnic University (UM6P), Benguerir, Morocco, is seeking for a postdoctoral candidate in the area of machine learning for IoT networks. The candidate must hold (or about to complete) a PhD in the related
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Career Development Shape the future of student employability through digital learning and content creation. Base salary will be in the range $95,361 - $102,302 + 17% Superannuation (HEW Level 06
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criteria. We allocate scholarships based on need. Students with the greatest need will receive the highest value scholarships. About the scholarship The Learning Potential Fund provides support through
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On-device machine learning (ML) is rapidly gaining popularity on mobile devices. Mobile developers can use on-device ML to enable ML features at users’ mobile devices, such as face recognition