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postdoctoral position in data analysis, where you will apply machine learning techniques to understand how resistance genes spread and to help detect infections caused by resistant bacteria. The position is part
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will do Take courses at an advanced level within the Graduate school of Machine and Vehicle Systems | Chalmers As a PhD student, your primary responsibility is to conduct research in shared control using
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fusion to address key environmental challenges. Strategically positioned to impact Earth observation science, we collaborate on satellite development, NewSpace technologies, and apply machine learning
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to learn Swedish, to facilitate teaching and research collaboration. Chalmers offers Swedish courses. Mandatory A PhD degree in a relevant field of research, awarded no more than three years prior
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interdisciplinary and to learn new skills and to perform research in collaboration with others. We seek candidates with the following qualifications: A doctoral degree in a Bioscience-related field awarded
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models into Chalmers’ bridge simulators in collaboration with other researchers. You are also expected to supervise PhD and MSc students and to publish at least two peer-reviewed journal articles during
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strong expertise in control theory, machine learning, and probability. You will also collaborate with: Vehicle Safety Division , which applies systems engineering and human factors to improve traffic
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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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-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning. Our department continuously strives to be an attractive employer. Equality
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, computational materials science, computer science, or a related field, awarded no more than three years prior to the application deadline*. Background in physics-based battery modelling and/or machine learning is