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postdoctoral fellows to perform cutting-edge research in AI for radiation therapy. Research areas include developing and implementing AI techniques for image-guided radiation therapy, such as image
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look forward to receiving your application! Do you have a background in machine learning and interested in telecommunications? You have a chance to contribute to development of sensing methods for new
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Prof. Neil Walton (Durham University, UK). The general aim of this project is to develop throughput-optimal entanglement distribution algorithms (both centralized and decentralized algorithms
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 11 days ago
candidate will develop independent and collaborative research in the area of Machine Learning, Natural Language Processing, and Algorithm Design, and work in a diverse cross-disciplinary team with researchers
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Posting Details Student Title Classification Information Quick Link https://chapman.peopleadmin.com/postings/39061 Job Number SE176424 Position Information Department or Unit Name Fowler School
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training datasets; Design and carry out laboratory experiments to produce representative experimental training data; Develop physics-informed machine learning algorithms, trained on both numerical
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, the CSATLab , our SW Simulators , and our Facilities . For further information, you may refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role Develop innovative methods and data-driven AI tools
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of this thesis focus on several key areas: - Detection and modeling of node mobility: Supervised learning models will be developed to identify mobility patterns based on radio indicators such as RSSI, SNR, and
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, including experimental design and reinforcement learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential
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are available to support conference travel and professional development. Duties & Responsibilities: • Successful candidates will develop and refine computational, mathematical, and statistical models