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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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Computer Science, Economics, FinTech and Financial Innovation, Mathematics, or a related field from the University of Cape Town. Strong background in game theory, mechanism design, microeconomics, or cryptographic
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and rural health staff informatics, coordinate the writing of ethical applications and reports, and contribute to writing publications and external grants. To be successful you will need: A PhD in
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. This exciting project will focus on designing, constructing, and testing synthetic cells with multiple sub-compartments. Just like their living counterparts (i.e. eukaryotic cells), synthetic cells with different
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is to address these challenges by developing innovative integrated chassis controllers and processes that seamlessly coordinate multiple actuators from the outset. The research will explore advanced AI
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is to address these challenges by developing innovative integrated chassis controllers and processes that seamlessly coordinate multiple actuators from the outset. The research will explore model-based
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. Development of multimodal AI models that fuse data from multiple types of sensors to accurately model and predict wind turbine blade damage. Establish and develop data science pipelines for wind turbine blade
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environment empowering our people to fulfil their personal and professional ambitions · Gender-friendly environment with multiple actions to attract, develop and retain women in science · 32 days
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-friendly environment with multiple actions to attract, develop and retain women in science · 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance