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. Requirements PhD degree in biochemistry or structural biology, or an exam which is judged comparable to a Swedish Ph.D in biochemistry or structural biology. The degree needs to be obtained by the time of
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of an excellent team of several PhD students, PostDocs, and Researchers working on different projects related to biotechnological methods for producing recombinant silk proteins, characterization of these, spinning
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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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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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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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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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degree (PhD), as required by the project Grant Agreement signed with the European Commission, at least one original publication in a peer-reviewed journal, a background in the relevant methods, a complete
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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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(PhD students, post-docs, researchers and teachers) and is located at the BMC-building (Biomedical Center). The expertise includes computational and experimental mechanics of biological tissues, where a
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial