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                look forward to receiving your application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems 
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                look forward to receiving your application! We are looking for a PhD student in AI and machine learning with a focus on generative machine learning methods for cyber security applications. Your work 
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                application! We are looking for a PhD student in AI and machine learning with a focus on generative machine learning methods for cyber security applications. Your work assignments The primary focus of this PhD 
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                international experience during their PhD. We offer a PhD student position to explore and develop Machine Learning models evolving over space and time and to make use of these models to understand 
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                learning, automatic control, computer vision, deep learning, and software engineering. Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's 
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                , contribute to a better world. We look forward to receiving your application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and 
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                combines: Fluid dynamics and heat transfer (theory and experiments), Computational modeling, and Machine learning / computer vision for data analysis and pattern recognition. The goal is to improve 
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                funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested developing new machine learning methods for precision medicine and 
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                and small, contribute to a better world. We look forward to receiving your application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with 
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                automata, and the mathematical and computational foundations of neural networks. Familiarity with the following areas is meritorious: machine learning, computational complexity, tree automata and tree