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to enable the development of new algorithms for clinical AI based on patient data from heterogeneous sources notably language/speech-based sources. The activity will focus on the development of a prototype
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and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous PhD project. In addition to electromagnetic geophysics
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. Researchers at Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By combining the mathematical and computational cultures, and the
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technological progress in our increasingly digital, data-driven world. Researchers in Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By
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information of the data to make a prediction using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms
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. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address
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to submit a professional development plan no later than one month after commencement of the postdoctoral period. It is expected that the successful candidate will be able to complete the project in
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particular to the development and validation of novel computational language models, algorithms, and tools for spoken language-based cognitive tests for low-resource languages, and their integration with
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collaborative skills. Applicants must be proficient in both written and oral English. Experience from one or several of the following areas is an advantage: Developing algorithms for CFD solvers (e.g. OpenFOAM
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