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you have a passion for research and are you interested in audio machine learning for technological and neuroscientific applications? Are you eager to tackle complex problems and to develop creative
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Research Infrastructure? No Offer Description Are you interested in a project at the interface between physics, machine learning and neuromorphic computing? Do you thrive for both fundamental and societal
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of visual decision-making, sensory uncertainty, and decision confidence. Research methods include computational modelling, brain imaging (fMRI, MEG), machine learning, behavioural methods, and other
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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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, 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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intelligence (AI). Are you excited to advance our scientific understanding of what a cognitive capacity is? Do you question the AI hype on the so-called human-like capacities of machines? Do you enjoy thinking
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for this include automated reverse engineering with state machine inference to spot flaws in the program logic, the LangSec (Language-theoretic Security) approach to structurally improve input handling, and security
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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
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, chemistry, biology, mathematics and computer sciences. FNWI encompasses seven research institutes, one of them being the Institute for Science in Society. Both in research and in education ISiS is actively
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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