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an advantage: Rodent social behaviour, empathy-related behaviour, aggression, fear, or reinforcement learning tasks. Computational modelling, Bayesian statistics, reinforcement learning models, or model-based
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identifying relevant entities (who did what, where), and inferring timelines (when, and in what order) and relations (e.g. links to specific countries or groups). A promising direction is to train or fine-tune
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inference), and automated machine learning. holding (or close to acquiring) a PhD degree in Computer Science, Artificial Intelligence or a closely related field; strong research vision and an academic mindset
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: - A PhD degree in optimization or systems and control theory. - A strong mathematical background and an interest in conducting theoretical research. - A proven track record. - Excellent English
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be able to track differences in strategy use between novices and experts on a task and map their learning trajectory. What are you going to do? You will be responsible for coordinating and carrying out
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Can technology learn to listen to how athletes feel, and not just to what the sensors measured? In the ASPIRE project, we develop knowledge for the new generation of sports tracking technology that
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on developing both the means and the metrics essential to monitoring trends, tracking changes, and enabling action to sustain biologically diverse environments and productive agricultural systems.
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micro/nano-robotic systems that mimic motion of organisms. Techniques would be developed to track and control the path of the novel devices using images (MR and ultrasound imaging modalities). You will
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attention and cognitive processing. You will work in a multidisciplinary team using cutting-edge experimental methods, including eye tracking, pupillometry and behavioural paradigms, to advance our
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industry. Our group combines precision experiments, advanced imaging, and modeling to uncover the physics of tin droplets under extreme conditions of laser irradiation. We have established a strong track