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., machine learning for quantum error prevention/mitigation/correction) Quantum machine learning Quantum cloud technologies We are actively involved in practical applications through partnerships with
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polar orbit, passing near the poles about 15 times per day and regularly observing the CIFAR study region. Its payload - two optical cameras, a thermal camera, and onboard machine-learning capabilities
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, etc.), and data-driven methods (optimisation, generative AI, agent-based modelling, machine learning). Our work provides decision support for policy makers, industry stakeholders, and researchers by
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years of post-PhD research and engineering experience in AI for mobile security Solid knowledge in adversarial machine learning or trustworthy AI, including experience with robustness assessment and
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the HNSCC team, including Taran Gujral (machine learning-enabled drug screening), Slobodan Beronja (mouse models of HNSCC), and Patrick Paddison (functional genomics). This work will encompass a broad array
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autonomous driving. Your profile Master's degree in Computer Science, Artificial Intelligence, Robotics, or related field Strong background in machine learning, deep learning, or computer vision Experience
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systems, with a focus on 3GPP compliant 5G/6G NR NTN OFDM waveforms Develop and analyse signal processing and/or machine learning algorithms for joint channel, delay, Doppler and carrier phase estimation
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wireless communications, RF signal processing, and/or applied machine learning Strong background in digital communications and RF signal processing, ideally with experience in SATCOM, NTNs, or space-borne
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intelligence (AI)-assisted image analysis for bioinformatics and medicine. The project is highly interdisciplinary, involving areas of microfluidics, fluidic mechanics, biomedical imaging, and machine learning
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uses long timescale molecular dynamics (MD) simulations, integrated with experimental observables (especially cryo-electron microscopy data), and machine learning tools to better capture the dynamics