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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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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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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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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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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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-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
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to the application deadline. PhD in computer science, electrical engineering, biomedical engineering, or a related field. Experience in Python programming, natural language processing, and multimodal deep learning
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passive and active flow control algorithms, potentially incorporating machine learning/AI, to enhance aerodynamic performance and stall delay with rapid response times. The research is conducted in