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CMFI Cluster of Excellence iFIT Cluster of Excellence Machine Learning CIN LEAD Graduate School & Research Network Collaborative Research Centers Transregional Collaborative Research Centers (CRC-TRRs
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CMFI Cluster of Excellence iFIT Cluster of Excellence Machine Learning CIN LEAD Graduate School & Research Network Collaborative Research Centers Transregional Collaborative Research Centers (CRC-TRRs
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academia and industry. Requirements The following qualifications are required: Solid knowledge in mathematics and statistics, in areas such as linear algebra, probability theory, machine learning, high
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Machine learning Experience is ideally shown through a thesis, seminar papers, or scientific publications. Alternatively, excellent grades in a respective Master’s programme. Strong intrinsic motivation
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2019, unites top PhD students in all areas of data-driven research and technology, including scalable storage, stream processing, data cleaning, machine learning and deep learning, text processing, data
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particularly valuable. Documented experience with machine learning and biostatistics is also highly meritorious.You can find information about education at postgraduate level, eligibility requirements and
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Project title: Privacy/Security Risks in Machine/Federated Learning systems Supervisory Team: Dr Han Wu Project description: In the wake of growing data privacy concerns and the enactment
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The molecular biosciences are undergoing a major paradigm shift – away from analysing individual genes and proteins to studying large molecular machines and cellular pathways, with the ultimate goal
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you will learn the specific methods you need for your project Feedback from experienced research advisers Excellent research facilities Instruction in English Thesis may be written in English or German
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world, and with world-class photonic facilities at Monash. "Quantum nanophotonic chip" "Multimode imaging through ultrathin meta-optics" "Advancing optical imaging with flat optics" "Machine-learning