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the sense of smell works in humans and build AI models of these. We seek a candidate who have experience working with time series data (EEG), signal processing and machine learning. PhD student 2 will work
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Engineering The project is in collaboration with a Swedish company for state-of-the-art statistical signal processing and machine learning based design and analysis of dynamical process and time-series. We will
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to two doctoral students with a very strong background and interest in system modeling, optimization, and machine learning. The successful candidate will join a MSCA Doctoral Network project on developing
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of Decision and Control Systems is currently looking for a doctoral student with a strong background and interest in machine learning, mathematics, and traffic models. The successful candidate will join a world
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development in Computer Vision - to extract 3D poses for animals in video, and in Machine Learning – to develop neural language models and methods for semi-supervised learning. Design and execution of data
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Communication Technology The doctoral student position focuses on fundamental research combining programming languages theory, compilers, and machine learning. In particular, the emphasis is on algorithms, formal
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, microeconomics and social learning to test the rationality of their decisions and understand the pitfalls commonly encountered when rational agents interact in an environment. Supervision: Prof. Cristian R. Rojas
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secure networked control systems. In particular, the focus will lie on the development of quantitative risk analysis tools for networked control systems with machine learning components and of algorithms
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the BioImage Model Zoo platform and related cloud-based infrastructure Collaborating with interdisciplinary teams on the Reef - Automated Imaging Farm. Implementing AI and machine learning methods for Bioimage
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an EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Human-Computer Interaction Inclusive Digital Learning