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computer scientists to design paradigms that compare "active" learning (standard VR) against "proprioceptive" learning (haptically guided movement), measuring outcomes such as path efficiency, force
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will develop an integrated framework combining computational fluid dynamics (CFD) with quantum gas LiDAR measurements to improve the quantification of methane emissions. The central research question is
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under relevant process conditions. Rational mutagenesis and computational protein design will then be applied to enhance lithium specificity and operational robustness in complex, high-impurity leachates
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or computer science is desirable but not required. An interest in interdisciplinary communication and engagement as well as an understanding of how AI is currently deployed in science is welcomed but not essential.
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Project summary Recent advances in artificial intelligence (AI) have fuelled the idea of building “AI scientists”, i.e., systems that can autonomously perform part or all of the research process. However, to realise this vision AI systems need specific abilities. One of these abilities is...