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tasks, supporting senior researchers and working across our national and international network. We expect the successful candidate to contribute to our unit’s already excellent reputation. The department
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neural networks, enabling us to estimate the reliability of a single decision of this algorithm. Regarding generalisation, recent self-supervised learning paradigms have strong synergies with the multi
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. Functional testing of developed PCBs, including experimental validation of electronic circuits and S-parameter characterization using a vector network analyzer (VNA).; 4. Experimental characterization
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
community at ANU. The successful candidates will join teams working on projects that span core AI research and interdisciplinary collaborations through the ANU Integrated AI Network (ai.anu.edu.au), focusing
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part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing . Further Information This full time, fixed term
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should be highly proficient with a range of machine learning approaches, including unsupervised, semi-supervised, supervised, and various deep learning techniques (e.g., convolutional neural networks
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
large, diverse employer. We are a recipient of the bronze award through the Science in Australia Gender Equity (SAGE) program and a platinum member of the Australian Network on Disability. We welcome
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Call for Outstanding Global Talents & Postdoctoral Fellows of Institute of Energy, Peking University
) Postdoctoral Fellows Application Form of Peking University Boya Postdoctoral Fellowship Two recommendation letters One explicit endorsement letter by the postdoc supervisor at Peking University More details
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research focus areas. The Research Fellow will embed their research expertise into the life of the School through the development of high-quality, productivity driven research networks across RMIT and with
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focus on honing expertise and research acumen in the areas of adolescent firearm injuries and death, mental health, traumatic stress, and defining trauma networks to identify children and young adults