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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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these systems operate in, ACPS increasingly rely on data-driven learning-enabled components to perform a variety of challenging decision-making tasks. While indispensable for autonomy, learning-enabled components
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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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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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computer. The WACQT team at Chalmers currently has about 100 members (faculty, permanent research staff, postdoctoral researchers, PhD students, and undergraduate students). WACQT is committed to promoting
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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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-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