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Field
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, computational modelling, and machine learning, and is well-suited for candidates eager to develop computational frameworks for next-generation structural dynamics and nanomechanical technologies. The vacant
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machine learning to improve outcome prediction and patient stratification. deepen our understanding of the etiology, clustering, and diagnostics of cardiovascular diseases in critically ill patients
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novel materials, tools, or artistic creations, humans instinctively explore the unknown in order to acquire information about it, to make sense of it, to act on it, and to appreciate what is in front of
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degree in Computer Science, Artificial Intelligence, Data Science, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong
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. The research will combine computational modeling (e.g., NLP, machine learning, deep learning) with human-centered research (e.g., user studies, experimental design, qualitative analysis). We are looking not only
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and research possible. PhD Opportunity: Engineering a Next Generation of Miniaturized In Vitro Models Our goal: Develop the next generation of miniaturized in vitro models to advance regenerative
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for uncovering nonlinearities and dissipation mechanisms, and design strategies for exploiting them. The project sits at the interface of nonlinear mechanics, computational modelling, and machine learning, and is
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students in the classroom, or helping shape everything that makes our education and research possible. PhD Opportunity: Engineering a Next Generation of Miniaturized In Vitro Models Our goal: Develop
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, or related field; Solid background in machine learning, deep learning and foundation models such as Large Language Models; Strong programming skills (Python/C++); Proven interest in generative models
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crucial; Design interventions to reduce bias and improve fairness and safety in human-AI interaction. The research will combine computational modeling (e.g., NLP, machine learning, deep learning) with human