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project "Machine-learning enhanced modeling of complex crack networks in anisotropic rail and wheel materials.” This exciting opportunity brings together computational and experimental material mechanics
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from automated vehicles (AVs), they must be both safe and appreciated by drivers. This project uses modeling (e.g., AI/machine learning) and human behavior data to predict perceived safety and quantify
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This is a broad call for five fully-funded PhD positions in computer science and engineering to work on machine learning, autonomous systems, software engineering, formal methods, and network
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of geometric deep learning and add rigorous arguments to a debate driven by empirical results. Who we are looking for We seek candidates with the following qualifications: To qualify as a PhD student, you must
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PhD in electrical engineering (or related field), with specialization in radio localization, radar, sensing, signal processing, or machine learning Have completed your PhD no more than three years
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on the hypothesis that the future of building design lies at the intersection of physically sound building simulation models and machine learning (ML) techniques. Key considerations include effectively integrating ML
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collaborative). Personal research synopsis for the PhD project (max 3 pages A4, font Arial 11 pt, single line spacing). It should be written and authored by yourself (not machine-generated e.g. using AI text
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of Computer Networks and Systems within the Department of Computer Science and Engineering . Within the Division we have four faculty members, four postdocs and eleven PhD students who are engaged in research
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passion for learning and a desire to work in a multidisciplinary and open team. Contract terms and what we offer The PhD-positions are fully funded from start As a PhD student at Chalmers, you are
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To fully benefit from automated vehicles (AVs), they must be both safe and appreciated by drivers. This post-doc is to use modeling (e.g., AI/machine learning) and behavior data to predict perceived