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for Science in Society (ISiS) as one of two PhD candidates! The first PhD project mainly involves a quantitative social science study of how the transformative developments affect the content of peer review
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, and decision confidence. Research methods include computational modelling, brain imaging (fMRI, MEG), machine learning, behavioural methods, and other techniques. Virtually every decision we make comes
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deeply and critically? If so, this position may be for you. In this PhD project, titled ’Cognitive capacities and machines: Why do calculators exist, if AGI cannot?’, you will adopt various meta
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you interested in a project at the interface between physics, machine learning and neuromorphic computing? Do you thrive for both fundamental and societal impact of your research? We have a project for
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learning techniques are increasingly required. The Radboud astrophysics group has extensive expertise, for example in star and stellar-population models; machine-learning techniques for the extraction
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communication for improving well-being. A key role is played by techniques and tools from the area of Artificial Intelligence: innovative methods such as machine learning and knowledge representation are used
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, machine learning, robotics and symbolic AI, Bachelor’s students are also trained in courses such as Theoretical Modelling for Cognitive Science, AI as a Science, or Human-Computer Interaction. In our
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this multidisciplinary PhD project supervised by Dr Mairieli Wessel and Prof. Frits Vaandrager, you will combine insights from software engineering, human-computer interaction and machine learning by applying empirical
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and the LOFAR radio telescope as well as SKA in the future. To fully understand this data, complex numerical simulations and machine learning techniques are increasingly required. The Radboud
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of supramolecular, peptide-based soft materials and connect this to machine learning to navigate the peptide sequence space, and to optimise the properties of promising candidates. In this project, you will use state